dr inż. Adam Brzeski
Employment
- Assistant professor at Department of Computer Architecture
Publications
Filters
total: 47
Catalog Publications
-
DEPTH IMAGES FILTERING IN DISTRIBUTED STREAMING
PublicationIn this paper we discuss the comparison of point cloud filters focusing on their applicability for streaming optimization. For the filtering stage within a stream pipeline processing we evaluate three filters: Voxel Grid, Pass Through and Statistical Outlier Removal. For the filters we perform series of the tests aiming at evaluation of changes of point cloud size and transmitting frequency (various fps ratio). We propose a distributed...
-
Depth Images Filtering In Distributed Streaming
PublicationIn this paper, we propose a distributed system for point cloud processing and transferring them via computer network regarding to effectiveness-related requirements. We discuss the comparison of point cloud filters focusing on their usage for streaming optimization. For the filtering step of the stream pipeline processing we evaluate four filters: Voxel Grid, Radial Outliner Remover, Statistical Outlier Removal and Pass Through....
-
Evaluating Performance and Accuracy Improvements for Attention-OCR
PublicationIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
-
Residual MobileNets
PublicationAs modern convolutional neural networks become increasingly deeper, they also become slower and require high computational resources beyond the capabilities of many mobile and embedded platforms. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity. In this paper, we propose a novel residual depth-separable convolution block, which is an improvement of the basic...
-
Towards Healthcare Cloud Computing
PublicationIn this paper we present construction of a software platform for supporting medical research teams, in the area of impedance cardiography, called IPMed. Using the platform, research tasks will be performed by the teams through computer-supported cooperative work. The platform enables secure medical data storing, access to the data for research group members, cooperative analysis of medical data and provide analysis supporting tools...
-
Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublicationOne of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. The problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier...
-
Real-Time Gastrointestinal Tract Video Analysis on a Cluster Supercomputer
PublicationThe article presents a novel approach to medical video data analysis and recognition. Emphasis has been put on adapting existing algorithms detecting le- sions and bleedings for real time usage in a medical doctor's office during an en- doscopic examination. A system for diagnosis recommendation and disease detec- tion has been designed taking into account the limited mobility of the endoscope and the doctor's requirements. The...
-
Real-Time Bleeding Detection in Gastrointestinal Tract Endoscopic Examinations Video
PublicationThe article presents a novel approach to medical video data analysis and recognition of bleedings. Emphasis has been put on adapting pre-existing algorithms dedicated to the detection of bleedings for real-time usage in a medical doctor’s office during an endoscopic examination. A real-time system for analyzing endoscopic videos has been designed according to the most significant requirements of medical doctors. The main goal of...
-
Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublicationImaging 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.
-
Semantic segmentation training using imperfect annotations and loss masking
PublicationOne 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...
-
Parameters optimization in medicine supporting image recognition algorithms
PublicationIn this paper, a procedure of automatic set up of image recognition algorithms' parameters is proposed, for the purpose of reducing the time needed for algorithms' development. The procedure is presented on two medicine supporting algorithms, performing bleeding detection in endoscopic images. Since the algorithms contain multiple parameters which must be specified, empirical testing is usually required to optimise the algorithm's...
-
Rozpoznawanie chorób układu pokarmowego z wykorzystaniem technik sztucznej inteligencji
PublicationCelem pracy jest przedstawienie i ocena algorytmów rozpoznawania chorób w filmach endoskopowych pod kątem możliwości ich zastosowania do budowy systemów automatycznego wykrywania chorób dla rzeczywistego wspomagania badań lekarskich. Porównano efektywność najnowszych algorytmów poprzez pomiar ich skuteczności w zaawansowanym środowisku testowym, zbudowanym w oparciu o materiały z filmów endoskopowych, opracowane we współpracy z...
-
Parallelization of video stream algorithms in kaskada platform
PublicationThe purpose of this work is to present different techniques of video stream algorithms parallelization provided by the Kaskada platform - a novel system working in a supercomputer environment designated for multimedia streams processing. Considered parallelization methods include frame-level concurrency, multithreading and pipeline processing. Execution performance was measured on four time-consuming image recognition algorithms,...
-
Moduł gier miejskich dla elektronicznego przewodnika multimedialnego EGIT
PublicationW artykule przedstawiono charakterystykę dostępnych rozwiązań i platform gier miejskich oraz dokonano ich porównania. Przedstawiono koncepcję definiowania funkcjonalności modułu gier miejskich stanowiącego rozszerzenie przewodnika eGIT. Opisano architekturę komponentową elektonicznego, bezprzewodowego, multimedialnego przewodnika eGIT wraz z modułem gier miejskich. Przedstawiono proces integracji modułu z aplikacją bazową eGIT,...
-
Konstrukcja bazy danych dla systemu wspomagania diagnostyki chorób przewodu pokarmowego
PublicationW artykule krótko przedstawiono charakterystykę procesu diagnostyki chorób przewodu pokarmowego oraz istniejące techniki wspomagania go na bazie analizy zdjęć z badań endoskopowych. Szczegółowo opisano proces tworzenia specjalistycznej bazy danych medycznych, której przeznaczeniem jest wspomaganie procesu uczenia klasyfikatorów chorób przewodu pokarmowego. Na koniec przedstawiono zebrane w bazie dane oraz uzyskane efekty.
-
Ocena skuteczności wybranych metod klasyfikacji statycznych i dynamicznych gestów rąk
PublicationW artykule przedstawiono porównanie technik sztucznej inteligencji w aspekcie rozpoznawania statycznych i dynamicznych gestów rąk. Jako urządzenie wejściowe posłużyła bezprzewodowa elektroniczna rękawica e-Glove. Gesty rozpoznawane są w procesie analizy wartości sygnałów pochodzących z magnetometru i akcelerometrów trójosiowych. W referacie przedstawiono porównanie skuteczności wybranych technik zastosowanych w rozpoznawaniu gestów...
-
Endoscopic Video Classification with the Consideration of Temporal Patterns
PublicationThe 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...
-
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...
-
An Overview of the Development of a Real-Time System for Endoscopic Video Classification
PublicationThe article presents the results of improving endoscopic image classification algorithms in an effort towards applying them in a real-time diagnosis supporting system. Methods for the detection and removal of personal data are presented and discussed. The currently developed recognition algorithms have been improved in terms of accuracy and performance to make them suitable for a real-life implementation. Their test results are...
-
Dependable Integration of Medical Image Recognition Components
PublicationComputer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....
seen 1395 times