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Search results for: THERMAL IMAGES
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Internet photogrammetry for inspection of seaports
PublicationThis paper intends to point out the possibility of using Internet photogrammetry to construct 3D models from the images obtained by means of UAVs (Unmanned Aerial Vehicles). The solutions may be useful for the inspection of ports as to the content of cargo, transport safety or the assessment of the technical infrastructure of port and quays. The solution can be a complement to measurements made by using laser scanning and traditional...
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The influence of image masks definition onsegmentation results of histopathological imagesusing convolutional neural network
PublicationAbstract—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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Color-based Detection of Bleeding in Endoscopic Images
PublicationIn this paper a color descriptor designed for bleeding detection in endoscopic images is proposed. The development of the algorithm was carried out on a representative training set of 36 images of bleeding and 25 clear images. Another 38 bleeding and 26 normal images were used in the final stage as a test set. All of the considered images were extracted from separate endoscopic examinations. The experiments include color distribution...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Influence of image transformations and quality degradations on SURF detector efficiency
PublicationA method for task-oriented examination of SURF keypoint detector accuracy is presented in the paper. It consists of generating test images, based on a given exemplar, processed by affine transformations: random rotation and scaling, and varying degree of degradations: darkening, blurring, noising, and compression. Details of applied degradation procedure are presented, followed by essentials of SURF-based images matching. A distance...
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Adaptive Method of Raster Images Compression and Examples of Its Applications in the Transport Telematic Systems
PublicationThe paper presents a concept and exemplary application of an adaptive method of compression of raster images which may be applied, i.a. in ITS systems. The described method allows to improve the efficiency of systems belonging to ITS category, which require transmission of large volumes of image data through telecommunications networks. The concept of the adaptive method of compression of raster images described in the paper uses...
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A new quaternion-based encryption method for DICOM images
PublicationIn this paper, a new quaternion-based lossless encryption technique for digital image and communication on medicine (DICOM) images is proposed. We have scrutinized and slightly modified the concept of the DICOM network to point out the best location for the proposed encryption scheme, which significantly improves speed of DICOM images encryption in comparison with those originally embedded into DICOM advanced encryption standard...
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublicationThis 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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Robustness of contact-less optical method, used for measuring contact wire position in changeable lighting conditions
PublicationThe article presents verification of robustness of contactless method based on 2D image camera, which is used to measure catenary contact wire position in changeable ambient lighting conditions. Robustness in changeable lighting conditions is ensured through the combination of advanced image processing for background information removal and the algorithm of error correction. This algorithm detects incorrect images and substitutes...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite 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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Smart Karyotyping Image Selection Based on Commonsense Knowledge Reasoning
PublicationKaryotyping 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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A method of selecting light sources from night satellite scenes
PublicationSatellite images carries a lot of data. Very sophisticated methods of analyses may reveal very complicated nature of the observed objects. In case of night images, lights play the role of information sources. In this paper we would like to present results of the research aimed to describe light sources from satellite night images by providing description of their luminosity. The authors point source imaging data from the satellite...
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Application of Shape From Shading Technique for Side Scan Sonar Images
PublicationSide scan sonar (SSS) is one of the most widely used imaging systems in the underwater environment. It is relatively cheap and easy to deploy in comparison with more powerful sensors like multibeam echosounder or synthetic aperture sonar. Although, the SSS does not provide directly the seafloor bathymetry measurements. Its outputs are usually in a form of grey level acoustic images of seafloor. However, the analysis of such images...
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Digital Fingerprinting based on Quaternion Encryption for Image Transmission
PublicationIn this paper a new digital fingerprinting scheme for images is proposed. A proposed method is based on quaternion encryption with Cipher Block Chaining (CBC) mode of operation. Quaternions are hyper-complex numbers of rank 4 and thus often applied to mechanics in three-dimensional space. The encryption algorithm is designed for grey-tone images. For purpose of encryption, the algorithm uses the rotation of data vectors presented...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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Reversible data hiding in encrypted DICOM images using sorted binary sequences of pixels
PublicationIn this paper, a novel reversible data hiding method for encrypted DICOM images is proposed. The method utilizes binary decomposition of the input data paired with a sorting process of the obtained binary sequences to ensure efficient data embedding in each predefined data block for specific most significant bit (MSB) planes while exploiting the properties of run-length encoding. The proposed scheme is lossless, and based on the...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublicationLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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PERFORMANCE OF ENDOSCOPIC IMAGE ANALYSIS ALGORITHMS IN LARGE BOWEL VIDEOS PROCESSING
PublicationComputer-assisted endoscopy is a rapidly developing eld of study. Many image anal- ysis algorithms exist, achieving very high rates of eciency at processing single endoscopic images. However, most of them were never tested in processing real-life endoscopic videos. In the article such tests of 16 endoscopy image analysis algorithms are presented and dis- cussed. Tests were performed on two real-life endoscopic videos of a human...
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Digital Fingerprinting Based on Quaternion Encryption Scheme for Gray-Tone Images
PublicationIn this paper a new idea of digital images fingerprinting is proposed. The method is based on quaternion encryption in the Cipher Block Chaining (CBC) mode. Quaternion sare hyper-complex numbers of rank 4 and thus often applied to mechanics in three-dimensional space. The encryption algorithm described in the paper is designed for gray-tone images but can easily be adopted for color ones. For the encryption purpose, the algorithm...
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Three-dimensional mapping for data collected using variable stereo baseline
PublicationThe paper describes a system of 3D mapping of data collected with due regard for variable baseline. This solution constitute an extension to a VisRobot sub-system developed as a subsystem, necessary for implementing the generic idea of using mobile robots to explore an indoor static environment. This subsystem is to acquire stereo images, calculate the depth in the images and construct the sought 3D map. Stereo images are obtained...
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User-generated images and its impact on consumer-based brand equity and on purchase intention
PublicationResearchers and brand managers have limited knowledge of the effects that different types of user-generated content (UGC) have on consumers’ perception of brands and behavior. In this study we investigated 301 authors of a specific category of UGC, i.e., user-generated images (UGI) on a social networking site to confirm the relationships of four drivers reported in literature (co-creation, empowerment, community, and self-concept)...
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From evil demiurge to caring hero: Images of geneticists in the movies
PublicationAlthough images of science and scientists depicted in popular culture have been criticized as an exaggeration and fear mongering, the cinema is an important resource that influences individuals’ beliefs about science. Because popular depictions of science play a crucial role in constructing the public’s ‘scientific imaginary’ they constitute an inherent dimension of the social understanding of science and are as important for...
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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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Underwater Acoustic Imaging of the Sea
PublicationAcoustic waves are a carrier of information mainly in environments where the use of other types of waves, for example electromagnetic waves, is limited. The term acoustical imaging is widely used in the ultrasonic engineering to imaging areas in which the acoustic waves propagate. In particular, ultrasound is widely used in the visualization of human organs - ultrasonography (Nowicki, 2010). Expanding the concept, acoustical imaging...
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Vehicle classification based on soft computing algorithms
PublicationExperiments and results regarding vehicle type classification are presented. Three classes of vehicles are recognized: sedans, vans and trucks. The system uses a non-calibrated traffic camera, therefore no direct vehicle dimensions are used. Various vehicle descriptors are tested, including those based on vehicle mask only and those based on vehicle images. The latter ones employ Speeded Up Robust Features (SURF) and gradient images...
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Using Disparity Map for Moving Object Position Estimation in Pan Tilt Camera Images
PublicationIn this paper we present the algorithm for rapid moving object position estimation in an images acquired from pan tilt camera. Detection of a moving object in a image acquired from a moving camera might be quite challenging. Standard methods that relay on analyzing two consecutive frames are not applicable due to the changing background. To overtake this problem we decided to evaluate the possibility of calculating a disparity...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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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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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Characteristics of an image sensor with early-vision processing fabricated in standard 0.35 µm CMOS technology
PublicationThe article presents measurement results of prototype integrated circuits for acquisition and processing of images in real time. In order to verify a new concept of circuit solutions of analogue image processors, experimental integrated circuits were fabricated. The integrated circuits, designed in a standard 0.35 µm CMOS technology, contain the image sensor and analogue processors that perform low-level convolution-based image...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Contour Analysis of Bleeding Regions in Endoscopic Images
PublicationThis paper investigates the problem of detecting bleeding regions in images acquired from endoscopic examinations of gastrointestinal tract. The purpose is to identify the characteristic features of bleeding areas' contours in order to develop an accurate method for discriminating between true bleeding regions and missed detections, which could lead to a significant reduction of the false alarm rate of existing blood-detection...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial 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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SIMULATIONS OF FRACTURE IN CONCRETE BEAMS UNDER BENDING USING A CONTINUUM AND DISCRETE APPROACH
PublicationThe paper describes two-dimensional meso-scale results of fracture in notched concrete beams under bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones and air voids. Within continuum mechanics, the simulations were carried out with the finite element method based on a isotropic damage constitutive model enhanced by a characteristic...
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MODELLING OF CONCRETE FRACTURE AT AGGREGATE LEVEL USING DEM BASED ON X-RAY mu CT IMAGES OF INTERNAL STRUCTURE
PublicationThe paper describes two-dimensional meso-scale numerical results of fracture in notched concrete beams under quasi-static three-point bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones (ITZs) and air voids. As a numerical approach, the discrete element method (DEM) was used. The concrete micro-structure in calculations was directly...
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Urban scene semantic segmentation using the U-Net model
PublicationVision-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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The Digital Tissue and Cell Atlas and the Virtual Microscope
PublicationWith the cooperation of the CI TASK (Center of lnformatics Tri-Citry Academic Supercomputer and network) and the Gdańsk University of Technology, the Medical University of Gdańsk undertook the creation of the Digital Tissue and Cell Atlas and the Virtual Microscope for the needs of the Bridge of Data project. In the beginning, an extensive collection of histological and cytological slides was carefully selected and prepared by...
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A CNN based coronavirus disease prediction system for chest X-rays
PublicationCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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Analyzing the Impact of Simulated Multispectral Images on Water Classification Accuracy by Means of Spectral Characteristics
PublicationRemote 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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Study on the Coastline Evolution in Sopot (2008–2018) Based on Landsat Satellite Imagery
PublicationThe coastline is the boundary between the water surface in a reservoir or watercourse and the land, which is characterised by high instability and functional diversity. For these reasons, research on coastal monitoring has been conducted for several decades. Currently, satellite images performed with synthetic aperture radars (SARs) are used to determine its course and variability together with high-resolution multispectral imagery...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe 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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3D seafloor reconstruction using data from side scan and synthetic aperture sonar
PublicationSide scan and synthetic aperture sonars are widely used imaging systems in the underwater environment. They are relatively cheap and easy to deploy, in comparison with more powerful sensors, like multibeam echosounders. Although side scan and synthetic aperture sonars does not provide seafloor bathymetry directly, their records are finally related to seafloor images. Moreover, the analysis of such images performed by human eye...
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Economical methods for measuring road surface roughness
PublicationTwo 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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Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublicationIn 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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Stereo Camera Upgraded to Equal Baseline Multiple Camera Set (EBMCS)
PublicationThe paper presents the results of using a set of five cameras called Equal Baseline Multiple Camera Set (EBMCS) for making 3D images, disparity maps and depth maps. Cameras in the set are located in the vicinity of each other and therefore the set can be used for the purpose of stereoscopy similarly as a stereo camera.EBMCS provides disparity maps and depth maps which have a better quality than these maps obtained with the use...
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Using Eye-tracking to get information on the skills acquisition by the radiology residents
PublicationThis paper describes the possibility of monitoring the progress of knowledge and skills acquisition by the students of radiology. It is achieved by an analysis of a visual attention distribution patterns during image-based tasks solving. The concept is to use the eye-tracking data to recognize the way how the radiographic images are read by recognized experts, radiography residents involved in the training program, and untrained...