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Search results for: image classification
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A study of nighttime vehicle detection algorithms
Open Research DataThis 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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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep 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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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599723671]
Open Research DataThis 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]
Open Research DataThis 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 [7220729599723171]
Open Research DataThis 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]
Open Research DataThis 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]
Open Research DataThis 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]
Open Research DataThis 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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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn 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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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599721941]
Open Research DataThis 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]
Open Research DataThis 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
PublicationPurpose: 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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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublicationA 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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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublicationRecently, 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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Marta Kuc-Czarnecka dr
PeopleMarta Kuc-Czarnecka is the deputy head of the Department of Statistics and Economics at the Faculty of Management and Economics of the Gdańsk University of Technology. She also serves as the Dean's proxy for AMBA accreditation. She is a co-founder of Rethinking Economics Gdańsk and a member of the Foundation Edward Lipiński for the promotion of pluralism in economic sciences. In 2018-2022, she was Eurofound’s quality of life and...
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A Mammography Data Management Application for Federated Learning
PublicationThis study aimed to develop and assess an application designed to enhance the management of a local client database consisting of mammographic images with a focus on ensuring that images are suitably and uniformly prepared for federated learning applications. The application supports a comprehensive approach, starting with a versatile image-loading function that supports DICOM files from various medical imaging devices and settings....
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Distributed Framework for Visual Event Detection in Parking Lot Area
PublicationThe 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
PublicationThe 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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Playback detection using machine learning with spectrogram features approach
PublicationThis 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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The Application of Satellite Image Analysis in Oil Spill Detection
PublicationIn 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
PublicationW 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
PublicationThe 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
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Seafloor Characterisation and Imaging Using Multibeam Sonar Data
PublicationThe 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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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublicationThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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Evaluation of a company’s image on social media using the Net Sentiment Rate
PublicationVast 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
PublicationThe 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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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth 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
PublicationA 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
PublicationIn 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
PublicationBenthic 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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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant 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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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: 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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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant 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
PublicationBackground: 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
Open Research DataData 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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Bias mitigation benchmark that includes two datasets
Open Research DataISIC-2020 is the largest skin lesion dataset divided into two classes -- benign and malignant. It contains 33126 dermoscopic images from over 2000 patients. The diagnoses were confirmed either by histopathology, expert agreement or longitudinal follow-up. The dataset was gathered by The International Skin Imaging Collaboration (ISIC) from several medical...
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Pedestrian accidents
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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
Open Research DataData 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):