Wyniki wyszukiwania dla: IMAGE CLASSIFICATION
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Image Classification Based on Video Segments
PublikacjaIn the dissertation a new method for improving the quality of classifications of images in video streams has been proposed and analyzed. In multiple fields concerning such a classification, the proposed algorithms focus on the analysis of single frames. This class of algorithms has been named OFA (One Frame Analyzed).In the dissertation, small segments of the video are considered and each image is analyzed in the context of its...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Combined method of multibeam sonar signal processing and image analysis for seafloor classification
PublikacjaThe combined approach to seafloor characterisation was investigated. It relies on calculation of several descriptors (parameters) related to seabed type using three types of multibeam sonar data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Акустическое изображение омонима этнического языка как входной элемент формальной классификации межъязыковой омонимии [The acoustic image of ethnic homonyms as an input element in formal classification of interlinguistic homonymy]
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Акустическое изображение омонима этнического языка как входной элемент формальной классификации межъязыковой омонимии [The acoustic image of ethnic homonyms as an input element in formal classification of interlinguistic homonymy]
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Piotr Szczuko dr hab. inż.
OsobyDr hab. inż. Piotr Szczuko w 2002 roku ukończył studia na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej zdobywając tytuł magistra inżyniera. Tematem pracy dyplomowej było badanie zjawisk jednoczesnej percepcji obrazu cyfrowego i dźwięku dookólnego. W roku 2008 obronił rozprawę doktorską zatytułowaną "Zastosowanie reguł rozmytych w komputerowej animacji postaci", za którą otrzymał nagrodę Prezesa Rady...
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The Hough transform in the classification process of inland ships
PublikacjaThis article presents an analysis of the possibilities of using image processing methods for feature extraction that allows kNN classification based on a ship’s image delivered from an on-water video surveillance system. The subject of the analysis is the Hough transform which enables the detection of straight lines in an image. The recognized straight lines and the information about them serve as features in the classification...
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublikacjaThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublikacjaArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Objects classification based on their physical sizes for detection of events in camera images
PublikacjaIn the paper, a method of estimation of the physical sizes of the objects tracked in the video surveillance system, and a simple module for object classification based on the estimated physical sizes, are presented. The results of object classification are then used for automatic detection of various types of events in the camera image.
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How to Sort Them? A Network for LEGO Bricks Classification
PublikacjaLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Systematic approach to binary classification of images in video streams using shifting time windows
Publikacjain the paper, after pointing out of realistic recordings and classifications of their frames, we propose a new shifting time window approach for improving binary classifications. We consider image classification in tewo steps. in the first one the well known binary classification algorithms are used for each image separately. In the second step the results of the previous step mare analysed in relatively short sequences of consecutive...
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
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seafloor characterisation combined approach using multibeam sonar echo signal processing and image analysis
PublikacjaThe authors propose the approach to seafloor characterisation which relies on the combined, concurrent use of two different techniques: (i) multibeam sonar image analysis and (ii) multibeam seabed echoes processing. The first technique is based on constructing the grey-level sonar images of the seabed extracted from the echoes received in the consecutive soundings. Then, the set of parameters describing the local region of sonar...
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Analyzing the Impact of Simulated Multispectral Images on Water Classification Accuracy by Means of Spectral Characteristics
PublikacjaRemote sensing is widely applied in examining the parameters of the state and quality of water. Spectral characteristics of water are strictly connected with the dispersion of electromagnetic radiation by suspended matter and the absorp-tion of radiation by water and chlorophyll a and b.Multispectral sensor ALI has bands within the ranges of electromagnetic radia-tion: blue and infrared, absent in sensors such as Landsat, SPOT,...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublikacjaDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Seafloor characterisation using multibeam sonar echo signal processing and image analysis
PublikacjaThe authors propose the approach to multibeam seafloor characterisation which relies on the combined, concurrent use of two different techniques of multibeam sonar data processing. The first one is based on constructing the grey-level sonar images of seabed using the echoes received in the consecutive beams. Then, the parameters describing the local region of sonar image, namely, the local standard deviation of a grey level, and...
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Multi-Aspect Quality Assessment Of Mobile Image Classifiers For Companion Applications In The Publishing Sector
PublikacjaThe paper presents the problem of quality assessment of image classifiers used in mobile phones for complimentary companion applications. The advantages of using this kind of applications have been described and a Narrator on Demand (NoD) functionality has been described as one of the examples, where the application plays an audio file related to a book page that is physically in front of the phone's camera. For such a NoD application,...
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LEGO bricks for training classification network
Dane BadawczeThe data set contains images of 447 different classes of LEGO bricks used for training LEGO bricks classification network. The dataset contains two types of images: photos (10%) and renders (90%) aggregated into respective directories. Each directory (photos and renders) contains 447 directories labeled as the official brick type number. The images...
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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublikacjaPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublikacjaThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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An Overview of the Development of a Real-Time System for Endoscopic Video Classification
PublikacjaThe article presents the results of improving endoscopic image classification algorithms in an effort towards applying them in a real-time diagnosis supporting system. Methods for the detection and removal of personal data are presented and discussed. The currently developed recognition algorithms have been improved in terms of accuracy and performance to make them suitable for a real-life implementation. Their test results are...
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On Algorithm Details in Multibeam Seafloor Classification
PublikacjaRemote sensing of the seafloor constitutes an important topic in exploration, management, protection and other investigations of the marine environment. In the paper, a combined approach to seafloor characterisation is presented. It relies on calculation of several descriptors related to seabed type using three different types of multibeam sonar data obtained during seafloor sensing, viz.: 1) the grey-level sonar images (echograms)...
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublikacjaSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublikacjaThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Mask Detection and Classification in Thermal Face Images
PublikacjaFace masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublikacjaThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublikacjaIn the paper, the approach to seafloor characterisation is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry and underwater object detection and imaging, are also the promising tool in seafloor characterization and classification, having several advantages over conventional single beam echosounders. The proposed approach relies on the combined, concurrent use...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublikacjaShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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ColorNephroNet: Kidney tumor malignancy prediction using medical image colorization
PublikacjaRenal tumor malignancy classification is one of the crucial tasks in urology, being a primary factor included in the decision of whether to perform kidney removal surgery (nephrectomy) or not. Currently, tumor malignancy prediction is determined by the radiological diagnosis based on computed tomography (CT) images. However, it is estimated that up to 16% of nephrectomies could have been avoided because the tumor that had been...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Improving automatic surveillance by sound analysis
PublikacjaAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Agnieszka Mikołajczyk-Bareła dr inż.
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Efficiency comparison of selected endoscopic video analysis algorithms
PublikacjaIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Deep neural networks for data analysis
Kursy OnlineThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Developmental odontogenic cysts - Male, 45 - Tissue image [6290730011491911]
Dane BadawczeThis is the histopathological image of GUM tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: VS200 Olympus slide scanner (20x magnification) and saved to DICOM format.
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Economical methods for measuring road surface roughness
PublikacjaTwo low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and...
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A study of nighttime vehicle detection algorithms
Dane BadawczeThis dataset is from my master's thesis "A study of nighttime vehicle detection algorithms". It contains both raw data and preprocessed dataset ready to use. In the pictures below you can see how images were annotated.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599723171]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599714301]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599717481]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599723671]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599723331]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599726571]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublikacjaIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599721941]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599721221]
Dane BadawczeThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Deep convolutional neural network for predicting kidney tumour malignancy
PublikacjaPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Marta Kuc-Czarnecka dr
OsobyMarta Kuc-Czarnecka jest zastępczynią kierownika Katedry Statystyki i Ekonomii na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. Pełni również funkcję pełnomocniczki Dziekana ds. akredytacji AMBA. Jest współzałożycielką Rethinking Economics Gdańsk oraz członkinią Fundacji im. Edwarda Lipińskiego na rzecz promocji pluralizmu w naukach ekonomicznych. W latach 2018-2022 była ekspertką Europejskiej Fundacji na Rzecz Poprawy...
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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublikacjaRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublikacjaA concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Distributed Framework for Visual Event Detection in Parking Lot Area
PublikacjaThe paper presents the framework for automatic detection of various events occurring in a parking lot basing on multiple camera video analysis. The framework is massively distributed, both in the logical and physical sense. It consists of several entities called node stations that use XMPP protocol for internal communication and SRTP protocol with Jingle extension for video streaming. Recognized events include detecting parking...
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Seafloor Characterisation Using Underwater Acoustic Devices
PublikacjaThe problem of seafloor characterisation is important in the context of management as well as investigation and protection of the marine environment. In the first part of the paper, a review of underwater acoustic technology and methodology used in seafloor characterisation is presented. It consists of the techniques based on the use of singlebeam echosounders and seismic sources, along with those developed for the use of sidescan...
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The Application of Satellite Image Analysis in Oil Spill Detection
PublikacjaIn recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to...
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Badanie stanu nawierzchni drogowej z wykorzystaniem uczenia maszynowego
PublikacjaW artykule opisano budowę systemu informowania o stanie nawierzchni drogowej z wykorzystaniem metod cyfrowego przetwarzania obrazów oraz uczenia maszynowego. Efektem wykonanych prac badawczych jest eksperymentalna platforma, pozwalająca na rejestrację uszkodzeń na drogach, system do analizy, przetwarzania i klasyfikacji danych oraz webowa aplikacja użytkownika do przeglądu stanu nawierzchni w wybranej lokalizacji.
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Video content analysis in the urban area telemonitoring system
PublikacjaThe task of constant monitoring of video streams from a large number of cameras and reviewing the recordings in order to find a specified event requires a considerable amount of time and effort from the system operators and it is prone to errors. A solution to this problem is an automatic system for constant analysis of camera images being able to raise an alarm if a predefined event is detected. The chapter presents various aspects...
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IEEE Information Theory Workshop on Detection, Estimation, Classification and Imaging
Konferencje -
Seafloor Characterisation and Imaging Using Multibeam Sonar Data
PublikacjaThe approach to seafloor characterisation and imaging is presented. It relies on the combined, concurrent use of several techniques of multibeam sonar data processing. The first one is based on constructing the grey-level sonar images of seabed using the backscattering strength calculated for the echoes received in the consecutive beams. Then, the set of parameters describing the local region of sonar image is calculated. The second...
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Evaluation of a company’s image on social media using the Net Sentiment Rate
PublikacjaVast amounts of new types of data are constantly being created as a result of dynamic digitization in all areas of our lives. One of the most important and valuable categories for business is data from social networks such as Facebook. Feedback resulting from the sharing of thoughts and emotions, expressed in comments on various products and services, is becoming the key factor on which modern business is based. This feedback is...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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SkinDepth - synthetic 3D skin lesion database
Dane BadawczeSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Bimodal classification of English allophones employing acoustic speech signal and facial motion capture
PublikacjaA method for automatic transcription of English speech into International Phonetic Alphabet (IPA) system is developed and studied. The principal objective of the study is to evaluate to what extent the visual data related to lip reading can enhance recognition accuracy of the transcription of English consonantal and vocalic allophones. To this end, motion capture markers were placed on the faces of seven speakers to obtain lip...
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Estimation of object size in the calibrated camera image = Estymacja rozmiaru obiektów w obrazach ze skalibrowanej kamery
PublikacjaIn the paper, a method of estimation of the physical sizes of the objects tracked by the camera is presented. First, the camera is calibrated, then the proposed algorithm is used to estimate the real width and height of the tracked moving objects. The results of size estimation are then used for classification of the moving objects. Two methods of camera calibration are compared, test results are presented and discussed. The proposed...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublikacjaBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublikacjaIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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The effect of impacted third molars on second molar external root resorption, a cross-sectional cone beam computed tomography study
PublikacjaBackground: Third molars have the highest prevalence of impaction in teeth and can cause pathological damage on the adjacent second molars. This study aims to evaluate the effects of factors related to impacted third molars on external root resorption (ERR) in adjacent second molars using cone-beam computed tomography (CBCT). Material and Methods: In CBCTs, the effect of impacted third molars on the root surface of adjacent second...
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - All accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Pedestrian accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Pedestrians. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Young drivers accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: young driver offender. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Motorcycle and moped accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: motorcyclists and mopeds. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Head-on accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: head-on. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Side-impact accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Side-impact. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Run off road accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Run off road. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Elderly people accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: elderly people (65+) - drivers, passengers and . vulnerable road user. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Cyclist accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Cyclists. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Night accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, time of accidents: Night. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Excessive speed accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, cause of accidents: Excessive speed accidents. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Child accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: children - drivers, passengers and . vulnerable road user.. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Alcohol and drug accidents
Dane BadawczeData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Offenders under influence of alcohol or drug - driver or pedestrian. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Medium to High and high road sections
Dane BadawczeData contain road sections with the highest number of accidents and victims on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019. Measures used to assess the level of risk is: minimum 4 accidents or 4 seriously injured or fatalities per one kilometer (5 classes: low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2019 - Municipality areas
Dane BadawczeData contain the number of accidents, victims, accident costs divided on municipality areas (119 areas) on regional roads (voivodeship roads) in pomorskie voivodeship in 2019. Measures used to assess the level of social risk are (5 classes: low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2019 - Poviat areas
Dane BadawczeData contain the number of accidents, victims, accident costs divided on poviat areas (16 areas) on regional roads (voivodeship roads) in pomorskie voivodeship in 2019. Measures used to assess the level of social risk are (5 classes low, low to medium, medium, medium to high, high):
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Surface EMG-based signal acquisition for decoding hand movements
Dane BadawczeBiosignal processing plays a crucial role in modern hand prosthetics. The challenge is to restore functionality of a lost limb based on the signals acquired from the surface of the stump. The number of sensors (emg channels) used for signal acquisition influence the quality of a prosthetic hand. Modern algorithms (including neural networks) can significantly...
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Microscopic examination of the texture of paper products
Dane BadawczeAtomic force microscopy (AFM) can be used to study the state of the paper fibers with the aim of providing qualitative and semi-quantitative information on degradation and aging. The work [1] reports the results of tests of various paper products subjected to deliberate aging processes under the influence of various factors. Chemical and biological...
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The surface of the sensor used in the analysis of odorous substances
Dane BadawczeHuman industrial activity usually leads to smaller or larger interference with the ecosystem, contributing to changes affecting the quality of life. An example may be the emission of gaseous substances, not necessarily toxic, but due to their intense smell, they can cause discomfort to people exposed to their inhalation. The problem is so important...