Wyniki wyszukiwania dla: SEGMENTATION
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Segmentation concept in mechanical engineering
PublikacjaZaprezentowano nowoczesne podejście do rozwiązywania problemów technicznych, technologicznych i organizacyjnych przedsiębiorstwa w oparciu ich strukturyzację. Przedstawiono przykłady segmentcji w stosunku do przedmiotów obrabianych oraz struktur organizacyjnych przedsiębiorstwa.
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Segmentation of the electric scooter market in Poland
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Instance segmentation of stack composed of unknown objects
PublikacjaThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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Segmentation of Passenger Electric Cars Market in Poland
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Dependence of Power Characteristics on Savonius Rotor Segmentation
PublikacjaSavonius rotors are large and heavy because they use drag force for propulsion. This leads to a larger investment in comparison to horizontal axis wind turbine (HAWT) rotors using lift forces. A simple construction of the Savonius rotor is preferred to reduce the production effort. Therefore, it is proposed here to use single-segment rotors of high elongation. Nevertheless, this rotor type must be compared with a multi-segment...
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Ensembling noisy segmentation masks of blurred sperm images
PublikacjaBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublikacjaSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublikacjaIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Image Segmentation of MRI image for Brain Tumor Detection
Publikacjathis research work presents a new technique for brain tumor detection by the combination of Watershed algorithm with Fuzzy K-means and Fuzzy C-means (KIFCM) clustering. The MATLAB based proposed simulation model is used to improve the computational simplicity, noise sensitivities, and accuracy rate of segmentation, detection and extraction from MR...
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RFM-based repurchase behavior for customer classification and segmentation
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Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review
PublikacjaThe segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...
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Urban scene semantic segmentation using the U-Net model
PublikacjaVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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MEAN SHIFT BASED SEGMENTATION FOR BLEEDING REGIONS IN ENDOSCOPIC VIDEOS
PublikacjaWith a set of 38 manually marked bleeding regions form endoscopic videos, the authors attempted to find an optimal image segmentation method for reproducing doctor’s markup. Mean shift segmentation combined with HSV histogram segmentation were used as a segmentation method, which was then optimized by tuning the parameters of the method using global optimization algorithm. A target function for measuring the quality of segmentation was...
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Accelerating Video Frames Classification With Metric Based Scene Segmentation
PublikacjaThis paper addresses the problem of the efficient classification of images in a video stream in cases, where all of the video has to be labeled. Realizing the similarity of consecutive frames, we introduce a set of simple metrics to measure that similarity. To use these observations for decreasing the number of necessary classifications, we propose a scene segmentation algorithm. Performed experiments have evaluated the acquired...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublikacjaIn this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...
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Examining Quality of Hand Segmentation Based on Gaussian Mixture Models
PublikacjaResults of examination of various implementations of Gaussian mix-ture models are presented in the paper. Two of the implementations belonged to the Intel’s OpenCV 2.4.3 library and utilized Background Subtractor MOG and Background Subtractor MOG2 classes. The third implementation presented in the paper was created by the authors and extended Background Subtractor MOG2 with the possibility of operating on the scaled version of...
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Comparison of image pre-processing methods in liver segmentation task
PublikacjaAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Multi-objective design of miniaturized impedance transformers by domain segmentation
PublikacjaFast multi-objective design optimization of compact microstrip impedance transformers is discussed. Our approach exploits approximation models constructed using sampled coarse- mesh EM simulation data in a partitioned design space and response correction techniques for design refinement. Demonstra
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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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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublikacjaIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublikacjaWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Application of colour image segmentation for localization and extraction text from images
PublikacjaW otaczającym nas świecie informacja tekstowa odgrywa wielką rolę. W postaci tekstowej podawane są: nazwy ulic, nazwy sklepów i instytucji, opisy przedmiotów np. tytuły książek, opakowań itp. Jednocześnie współczesne programy komputerowe służące do rozpoznawania tekstu (OCR) ''nie radzą sobie'' z analizą obrazów otrzymanaych za pomocą kamer. Segmentacja obrazu z następującą kontekstową analizą parametrów segmentów może dostarczyć...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublikacjaAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublikacjaMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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KEMR-Net: A Knowledge-Enhanced Mask Refinement Network for Chromosome Instance Segmentation
PublikacjaThis article proposes a mask refinement method for chromosome instance segmentation. The proposed method exploits the knowledge representation capability of Neural Knowledge DNA (NK-DNA) to capture the semantics of the chromosome’s shape, texture, and key points, and then it uses the captured knowledge to improve the accuracy and smoothness of the masks. We validate the method’s effectiveness on our latest high-resolution chromosome...
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Leveraging spatio-temporal features for joint deblurring and segmentation of instruments in dental video microscopy
PublikacjaIn dentistry, microscopes have become indispensable optical devices for high-quality treatment and micro-invasive surgery, especially in the field of endodontics. Recent machine vision advances enable more advanced, real-time applications including but not limited to dental video deblurring and workflow analysis through relevant metadata obtained by instrument motion trajectories. To this end, the proposed work addresses dental...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublikacjaAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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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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C2 NIWA Community-Segmentation Criteria and Building Brand Associations on the Example of a Selected Target Group
PublikacjaEvery organization which offers products or services wishes to communicate with their customers in the most effective way. This kind of communication is based on proper selection of target groups, which are extracted in the process of market segmentation. That is way it is very important to ask the question to whom the message is to be directed and what kind of message we want to give. This article describes the selection criteria...
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High-Speed Binary-to-Residue Converter Design Using 2-Bit Segmentation of the Input Word
PublikacjaIn this paper a new approach to the design of the high-speed binary-to-residue converter is proposed that allows the attaining of high pipelining rates by eliminating memories used in modulo m generators. The converter algorithm uses segmentation of the input binary word into 2-bit segments. The use and effects of the input word segmentation for the synthesis of converters for five-bit moduli are presented. For the number represented...
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Segmentation of academic community for the purposes of mobility plan development – case study of Gdansk University of Technology
PublikacjaThe objective of the paper is to analyse the structure of academic community for its transport behaviour and attitudes using the example of the Gdansk University of Technology (the GUT) in Poland. Once understood, the group can be divided into homogenous sub-groups and studied for their potential and ways to influence their behaviour, attitudes and transport patterns. The results may be used to develop dedicated actions designed...
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Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing
PublikacjaSolution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into one system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixellevel difference from the continually updated background model utilizing a Gaussian mixture calculated separately for every pixel. The shadow detection...
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Fast and accurate vision-based pattern detection and identification using color and grey image segmentation
PublikacjaPraca opisuje niewymagającą obliczeniowo metodę wykrywania i identyfikacji robotów mobilnych, która może być wykorzystywana w zawodach gry robotów w piłkę nożną. Wykrywanie robotów opiera się na przetwarzaniu obrazu otrzymanego z kamery. Zasadniczym elementem przetwarzania obrazu jest jego segmentacja opierająca się na rozpoznaniu koloru w systemie HSI.
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Dane BadawczeMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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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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MSIS sonar image segmentation method based on underwater viewshed analysis and high-density seabed model
PublikacjaHigh resolution images of Mechanically Scanned Imaging Sonars can bring detailed representation of underwater area if favorable conditions for acoustic signal to propagate are provided. However to properly asses underwater situation based solely on such data can be challenging for less than proficient interpreter. In this paper we propose a method to enhance interpretative potential of MSIS image by dividing it in to subareas depending...
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Application of data segmentation and segregation in alarm dedicated glass breaks detection method,based on Wavelet Transformatio
PublikacjaAutor opracowuje nowoczesną, dedykowaną dla systemów alarmowych, metodę bezkontaktowej detekcji zbicia szyby, bazującą na analizie sygnałów akustycznych i transformacji falkowej. Struktura badanego sygnału oraz pierwotne metody mające zastosowanie w fazie badawczej projektu przedstawione zostały we wcześniejszych publikacjach autora [1] i [2]. Ze względu na ich dużą złożoność obliczeniowe i przetwarzanie off-line nie mogły być...
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What are the true volumes of SEGA tumors? Reliability of planimetric and popular semi-automated image segmentation methods
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublikacjaSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Reliable low-cost surrogate modeling and design optimisation of antennas using implicit space mapping with substrate segmentation
PublikacjaAbstract: In this work, a reliable methodology for fast simulation-driven design optimisation of antenna structures is proposed. The authors’ approach exploits implicit space mapping (ISM) technology. To adopt it for handling antenna structures, they introduce substrate segmentation with separate dielectric permittivity value assigned for each segment as ISM preassigned parameters. At the same time, the coarse model for space mapping...
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublikacjaPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublikacjaOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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The Effectiveness of Semi-Automated and Fully Automatic Segmentation for Inferior Alveolar Canal Localization on CBCT Scans: A Systematic Review
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Multi-objective design optimization of antennas for reflection, size, and gain variability using kriging surrogates and generalized domain segmentation
PublikacjaCost-efficient multi-objective design optimization of antennas is presented. The framework exploits auxiliary data-driven surrogates, a multi-objective evolutionary algorithm for initial Pareto front identification, response correction techniques for design refinement, as well as generalized domain segmentation. The purpose of this last mechanism is to reduce the volume of the design space region that needs to be sampled in order...
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Detection of molecular signatures of oral squamous cell carcinoma and normal epithelium - application of a novel methodology for unsupervised segmentation of imaging mass spectrometry data
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Vident-lab: a dataset for multi-task video processing of phantom dental scenes
Dane BadawczeWe introduce a new, asymmetrically annotated dataset of natural teeth in phantom scenes for multi-task video processing: restoration, teeth segmentation, and inter-frame homography estimation. Pairs of frames were acquired with a beam splitter. The dataset constitutes a low-quality frame, its high-quality counterpart, a teeth segmentation mask, and...
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Assessment of particular abdominal aorta section extraction from contrast-enhanced computed tomography angiography
PublikacjaThe aim of this work is to improve the accuracy of extraction of a particular abdominal aorta section and to reduce the distortion in three-dimensional Computed Tomography Angiography (CTA) images. Imaging modality and quality plays crucial role in the medical diagnostic process, thus ensuring high quality of images is essential at every stage of acquisition and processing.Noise is defined as a disturbance of the image quality...
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The influence of image masks definition onsegmentation results of histopathological imagesusing convolutional neural network
PublikacjaAbstract—In the era of collecting large amounts of tissue materials, assisting the work of histopathologists with various electronic and information IT tools is an undeniable fact. The traditional interaction between a human pathologist and the glass slide is changing to interaction between an AI pathologist with a whole slide images. One of the important tasks is the segmentation of objects (e.g. cells) in such images. In this...
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Identification of Emotions Based on Human Facial Expressions Using a Color-Space Approach
PublikacjaHCI technology improves human-computer interaction. Such communication can be carried out with the use of emotions that are visible on the human face since birth. In this paper the Emotion system for detecting and recognizing facial expressions, developed in the MSc work, is presented. The system recognizes emotion from webcam video in real time. It is based on color segmentation and morphological operations. The system uses a...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Smart Karyotyping Image Selection Based on Commonsense Knowledge Reasoning
PublikacjaKaryotyping requires chromosome instances to be segmented and classified from the metaphase images. One of the difficulties in chromosome segmentation is that the chromosomes are randomly positioned in the image, and there is a great chance for chromosomes to be touched or overlap with others. It is always much easier for operators and automatic programs to tackle images without overlapping chromosomes than ones with largely overlapped...
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Shape-Based Pose Estimation of Robotic Surgical Instruments
PublikacjaWe describe a detector of robotic instrument parts in image-guided surgery. The detector consists of a huge ensemble of scale-variant and pose-dedicated, rigid appearance templates. The templates, which are equipped with pose-related keypoints and segmentation masks, allow for explicit pose estimation and segmentation of multiple end-effectors as well as fine-grained non-maximum suppression. We train the templates by grouping examples...
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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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Detection of the Oocyte Orientation for the ICSI Method Automation
PublikacjaAutomation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...
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Expedited Multi-Objective Design Optimization of Miniaturized Microwave Structures Using Physics-Based Surrogates
PublikacjaIn this paper, a methodology for fast multi-objective design optimization of compact microwave circuits is presented. Our approach exploits an equivalent circuit model of the structure under consideration, corrected through implicit and frequency space mapping, then optimized by a multi-objective evolutionary algorithm. The correction/optimization of the surrogate is iterated by design space confinement and segmentation based on...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Essential thrombocythemia - Female, 68 - Tissue image [11290630017295411]
Dane BadawczeThis is the histopathological image of HEMATOPOIETIC AND RETICULOENDOTHELIAL SYSTEMS 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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Essential thrombocythemia - Female, 68 - Tissue image [11290630017294601]
Dane BadawczeThis is the histopathological image of HEMATOPOIETIC AND RETICULOENDOTHELIAL SYSTEMS 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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Essential thrombocythemia - Female, 68 - Tissue image [11290630017291241]
Dane BadawczeThis is the histopathological image of HEMATOPOIETIC AND RETICULOENDOTHELIAL SYSTEMS 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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Pipelined division of signed numbers with the use of residue arithmetic for small number range with the programmable gate array
PublikacjaIn this work an architecture of the pipelined signed residue divider for the small number range is presented. Its operation is based on reciprocal calculation and multiplication by the dividend. The divisor in the signed binary form is used to compute the approximated reciprocal in the residue form by the table look-up. In order to limit the look-up table address an algorithm based on segmentation of the divisor into two segments...
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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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Three-dimensional modeling and automatic analysis of the human nasal cavity and paranasal sinuses using the computational fluid dynamics method
PublikacjaPurpose The goal of this study was to develop a complete workflow allowing for conducting computational fluid dynam- ics (CFD) simulation of airflow through the upper airways based on computed tomography (CT) and cone-beam computed tomography (CBCT) studies of individual adult patients. Methods This study is based on CT images of 16 patients. Image processing and model generation of the human nasal cavity and paranasal sinuses...
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Pipelined division of signed numbers with the use of residue arithmetic in FPGA
PublikacjaAn architecture of a pipelined signed residue divider for small number ranges is presented. The divider makes use of the multiplicative division algorithm where initially the reciprocal of the divisor is calculated and subsequently multiplied by the dividend. The divisor represented in the signed binary form is used to compute the approximated reciprocal in the residue form by the table look-up. In order to reduce the needed length...
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Karol Flisikowski dr inż.
OsobyKarol Flisikowski jest profesorem uczelni w Katedrze Statystyki i Ekonometrii, Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej. Jest odpowiedzialny jest za prowadzenie zajęć ze statystyki opisowej i matematycznej (w języku polskim i angielskim), a także badań naukowych w zakresie statystyki społecznej. Był uczestnikiem wielu konferencji o zasięgu krajowym, jak i międzynarodowym, gdzie prezentował wyniki prowadzonych przez...
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Automatic Threat Detection for Historic Buildings in Dark Places Based on the Modified OptD Method
PublikacjaHistoric buildings, due to their architectural, cultural, and historical value, are the subject of preservation and conservatory works. Such operations are preceded by an inventory of the object. One of the tools that can be applied for such purposes is Light Detection and Ranging (LiDAR). This technology provides information about the position, reflection, and intensity values of individual points; thus, it allows for the creation...
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An Overview of Image Analysis Techniques in Endoscopic Bleeding Detection
PublikacjaAuthors review the existing bleeding detection methods focusing their attention on the image processing techniques utilised in the algorithms. In the article, 18 methods were analysed and their functional components were identified. The authors proposed six different groups, to which algorithms’ components were assigned: colour techniques, reflecting features of pixels as individual values, texture techniques, considering spatial...
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Investigations of speech signal parameters with regard to articulation influences
PublikacjaW pracy zostało podjęte zagadnienie parametryzacji sygnału mowy w kontekście ekstrakcji cech biometrycznych. Analizowane parametry to parametry cepstralne (cepstrum liniowe i mel-cepstrum, czyli MFCC), parametry liniowej predykcji (LPC) oraz momenty widmowe i parametr F0. Zastosowano analize w krótkich stałych segmentach sygnału z zastosowaniem dużego zakładkowania, tzw. ''implicite segmentation''. Umożliwiło to zaobserwowanie...
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Akustyczna analiza natężenia ruchu drogowego dla systemów zarządzania ruchem
PublikacjaW pracy przybliżono wybrane zagadnienia z dziedziny zarządzania transportem drogowym w Polsce i na świecie. W tym kontekście pzredstawiono potrzeby rynkowe, wymagania jak i możliwości w zakresie pozyskiwania informacji o aktualnym stanie sieci drogowych. Zaproponowano akustyczną metodę nadzorowania ruchu drogowego i jej możliwości w kontekście systemów zarządzania ruchem. Przedstawiono schemat akwizycji sygnału wraz z danymi odniesienia....
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ARTIFICIAL MODEL IN THE ASSESSMENT OF THE ALGORITHM OF OBJECTS RECORDED BY LASER SCANNING SHAPE DETECTION (ALS/TLS)
PublikacjaBrief description of the study and used methods. Brief description of the study and used As part of the preparatory work aimed to create the application solution allowing for the automation of searching objects in data, obtained in the scanning process using ALS (Airborne Laser Scanning) or TLS (Terrestrial Laser Scanning), the authors prepared a artificial (synthetic, theoretical) model of space, used for the verification of operation...
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Vehicle detector training with minimal supervision
PublikacjaRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...
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Improving methods to calculate the loss of ecosystem services provided by urban trees using LiDAR and aerial orthophotos
PublikacjaIn this paper we propose a methodology for combining remotely sensed data with field measurements to assess selected tree parameters (diameter at breast height (DBH) and tree species) required by the i-Tree Eco model to estimate ecosystem services (ES) provided by urban trees. We determined values of ES provided by trees in 2017 in Racibórz (a city in South Poland) and estimated the loss of ES from January 1, 2017 to March 5, 2017,...
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Controlling computer by lip gestures employing neural network
PublikacjaResults of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....
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Human-Computer Interface Based on Visual Lip Movement and Gesture Recognition
PublikacjaThe multimodal human-computer interface (HCI) called LipMouse is presented, allowing a user to work on a computer using movements and gestures made with his/her mouth only. Algorithms for lip movement tracking and lip gesture recognition are presented in details. User face images are captured with a standard webcam. Face detection is based on a cascade of boosted classifiers using Haar-like features. A mouth region is located in...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublikacjaThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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Impact of Shifting Time-Window Post-Processing on the Quality of Face Detection Algorithms
PublikacjaWe consider binary classification algorithms, which operate on single frames from video sequences. Such a class of algorithms is named OFA (One Frame Analyzed). Two such algorithms for facial detection are compared in terms of their susceptibility to the FSA (Frame Sequence Analysis) method. It introduces a shifting time-window improvement, which includes the temporal context of frames in a post-processing step that improves the...
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Hazard Control in Industrial Environments: A Knowledge-Vision-Based Approach
PublikacjaThis paper proposes the integration of image processing techniques (such as image segmentation, feature extraction and selection) and a knowledge representation approach in a framework for the development of an automatic system able to identify, in real time, unsafe activities in industrial environments. In this framework, the visual information (feature extraction) acquired from video-camera images and other context based gathered...
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Endoscopic Video Classification with the Consideration of Temporal Patterns
PublikacjaThe article describes a novel approach to automatic recognition and classification of diseases in endoscopic videos. Current directions of research in this field are discussed. Most presented methods focus on processing single frames and do not take into consideration the temporal relationship between continuous classifications. Existing approaches that consider the temporal structure of an incoming frame sequence are focused on...
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MRI-Derived Subcutaneous and Visceral Adipose Tissue Reference Values for Children Aged 6 to Under 18 Years
PublikacjaThe assessment of body composition in pediatric population is essential for proper nutritional support during hospitalization. However, currently available methods have limitations. This study aims to propose a novel approach for nutrition status assessment and introduce magnetic resonance imaging (MRI)-derived subcutaneous and visceral fat normative reference values. A total of 262 healthy subjects aged from 6 to 18 years underwent...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Workforce mobility against the background of labour market duality theory – the example of selected OECD countries
PublikacjaThe paper aims to present an empirical study of labour market segmentation (LMS) hypothesis. According to the dual labour market theory jobs can be divided into two groups: primary and secondary jobs, with enter barriers into the first one. The primary jobs are usually described with relative high wages, whereas secondary jobs provide lower level of wages. In this paper we first examine the main sectors (according to the ISIC rev....
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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublikacjaThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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Identification of Emotional States Using Phantom Miro M310 Camera
PublikacjaThe purpose of this paper is to present the possibilities associated with the use of remote sensing methods in identifying human emotional states, and to present the results of the research conducted by the authors in this field. The studies presented involved the use of advanced image analysis to identify areas on the human face that change their activity along with emotional expression. Most of the research carried out in laboratories...
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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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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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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublikacjaArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...