Wyniki wyszukiwania dla: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES - MOST Wiedzy

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Wyniki wyszukiwania dla: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES

Wyniki wyszukiwania dla: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES

  • Robust Object Detection with Multi-input Multi-output Faster R-CNN

    Publikacja

    Recent 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

    Publikacja

    Recent 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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  • Reversible Video Stream Anonymization for Video Surveillance Systems Based on Pixels Relocation and Watermarking

    Publikacja

    A method of reversible video image regions of interest anonymization for applications in video surveillance systems is described. A short introduction to theanonymization procedures is presented together with the explanation of its relation to visual surveillance. A short review of state of the art of sensitive data protection in media is included. An approach to reversible Region of Interest (ROI) hiding in video is presented,...

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  • Some Security Features of Selected IoT Platforms

    Publikacja

    - TASK Quarterly - Rok 2020

    IoT (Internet of Things) is certainly one of the leading current and future trends for processing in the current distributed world. It is changing our life and society. IoT allows new ubiquitous applications and processing, but, on the other hand, it introduces potentially serious security threats. Nowadays researchers in IoT areas should, without a doubt, consider and focus on security aspects. This paper is aimed at a high-level...

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  • Why is TASK Quarterly a Significant Journal to Publish Your Article? —A Bibliometric Analysis of a Scientific and Technical Journal

    Publikacja

    A bibliometric analysis of TASK Quarterly in the years 1997-2021 in terms of various bibliometric indicators was performed to celebrate the 25th anniversary of the publication of the first issue of the journal. The number of publications and citations increased over the mentioned span of years. The leading countries in terms of the greatest number of papers published in TASK Quarterly are Poland, Italy, Germany, Ukraine, USA and...

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  • Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network

    Publikacja

    - Rok 2024

    Designing microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...

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  • Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches

    Publikacja
    • S. Gharsellaoui
    • M. Mansouri
    • S. Refaat
    • H. Abu-Rub
    • H. Messaoud

    - ENERGIES - Rok 2020

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  • Discovering Rule-Based Learning Systems for the Purpose of Music Analysis

    Publikacja

    Music analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...

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  • Superresolution algorithm to video surveillance system

    Publikacja

    - Rok 2010

    An application of a multiframe SR (superresolution) algorithm applied to video monitoring is described. The video signal generated by various types of video cameras with different parameters and signal distortions which may be very problematic for superresolution algorithms. The paper focuses on disadvantages in video signal which occur in video surveillance systems. Especially motion estimation and its influence on superresolution...

  • Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study

    Publikacja

    - Mechanical Systems and Signal Processing - Rok 2022

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  • Improvement of Task Management with Process Models in Small and Medium Software Companies

    Publikacja

    Small and medium software companies exhibit many special features that give reason for a dedicated approach to process improvement. They often cannot afford implementing maturity models or quality standards both in terms of time and money. Instead, they expect simpler solutions that can allow to run projects in more systematic and repeatable way, increase quality and knowledge management. In this paper, we present a method focused...

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  • PCBs in fish from southern Baltic Sea: Levels, bioaccumulation features and temporal trends during the 1997-2006 period

    Publikacja

    - MARINE POLLUTION BULLETIN - Rok 2009

    W próbkach 5 gatunków ryb bałtyckich pobranych w latach 1997-2006 oznaczono zawartość 7 wskaźnikowych polichlorowanych bifenyli. Zaobserwowano wyraźny trend spadku zawartości cięższych kongenerów w latach 1997-2001 dla różnych gatunków ryb za wyjątkiem dorsza. W próbkach szprota i śledzia stwierdzona statystycznie istotny spadek zawartości PCB 101, 118, 153, 138 i 180. Stwierdzono występowanie gatunkowospecyficznej bioakumulacji...

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  • Human memory enhancement through electrical stimulation in the temporal cortex

    Publikacja
    • M. T. Kucewicz
    • B. M. Berry
    • L. R. Miller
    • F. Khadjevand
    • Y. Ezzyat
    • J. M. Stein
    • V. Kremen
    • B. H. Brinkmann
    • P. Wanda
    • M. R. Sperling... i 10 innych

    - Brain: A Journal of Neurology - Rok 2018

    Direct electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement...

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  • Piotr Szczuko dr hab. inż.

    Dr hab. inż. Piotr Szczuko w 2002 roku ukończył studia na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej zdobywając tytuł magistra inżyniera. Tematem pracy dyplomowej było badanie zjawisk jednoczesnej percepcji obrazu cyfrowego i dźwięku dookólnego. W roku 2008 obronił rozprawę doktorską zatytułowaną "Zastosowanie reguł rozmytych w komputerowej animacji postaci", za którą otrzymał nagrodę Prezesa Rady...

  • The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video

    Publikacja
    • P. Szymak
    • P. Piskur
    • K. Naus

    - Remote Sensing - Rok 2020

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  • Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces

    Coding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...

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  • Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France

    Publikacja
    • N. N. Navnath
    • K. Chandrasekaran
    • A. Stateczny
    • V. M. Sundaram
    • P. Panneer

    - Remote Sensing - Rok 2022

    Current Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...

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  • E-learning courses

    Kursy Online
    • A. Wardziński
    • G. Gołaszewski
    • T. Zawadzka
    • A. Karpus
    • M. Wróbel
    • A. Przybyłek
    • W. Waloszek
    • A. Landowska
    • K. Goczyła

    Strona zawiera zbiór kursów prowadzonych metodą e-learning. Kursy te są skierowane do studentów I stopnia kierunku informatyka na VII semestrze profilu Bazy danych, do studentów na kierunku informatyka na II semestrze studiów II stopnia na specjalności ZAD i ISI.

  • Atomic Force Microscope data post-processing algorithm for higher harmonics imaging

    Previous works have proved that higher harmonics topography imaging using atomic force microscope (AFM) can significantly enhanced its measurement capabilities. Integrated tools dedicated to most of microscopes allow to visualize the investigated surface only by one selected harmonic. Because of the different characteristics of a sample, scanning tip and the environment, appropriate harmonic selection is time consuming and requires...

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  • BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising

    Denoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...

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  • Image Segmentation of MRI image for Brain Tumor Detection

    Publikacja

    - Rok 2020

    this 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...

  • Organochlorine pesticides in fish from the southern Baltic Sea: levels, bioaccumulation features and temporal trends during the 1995-2006 period

    Publikacja

    - MARINE POLLUTION BULLETIN - Rok 2008

    W próbkach pięciu gatunków ryb bałtyckich pobranych w latach 1995-2006 oznaczono zawartość heksachlorocykloheksanu (HCH), heksachlorobenzenu (HCB) oraz DDT i jego pochodnych. Dzięki zastosowaniu szeregu metod chemometrycznych a w szczególności analizy głównych składowych (PCA) zaobserwowano szereg istotnych zależności. Nie stwierdzono wpływu miejsca połowu na poziom analizowanych pestycydów w ciałach ryb. Zaobserwowano statystycznie...

  • C2 NIWA Community-Segmentation Criteria and Building Brand Associations on the Example of a Selected Target Group

    Publikacja

    Every 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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  • Systematic approach to binary classification of images in video streams using shifting time windows

    in the paper, after pointing out of realistic recordings and classifications of their frames, we propose a new shifting time window approach for improving binary classifications. We consider image classification in tewo steps. in the first one the well known binary classification algorithms are used for each image separately. In the second step the results of the previous step mare analysed in relatively short sequences of consecutive...

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  • Selection of Relevant Features for Text Classification with K-NN

    In this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...

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  • Left Temporal Lobe Arachnoid Cyst Presenting with Symptoms of Psychosis

    Publikacja

    - Rok 2021

    This...

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  • Image Classification Based on Video Segments

    Publikacja

    - Rok 2018

    In the dissertation a new method for improving the quality of classifications of images in video streams has been proposed and analyzed. In multiple fields concerning such a classification, the proposed algorithms focus on the analysis of single frames. This class of algorithms has been named OFA (One Frame Analyzed).In the dissertation, small segments of the video are considered and each image is analyzed in the context of its...

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  • Training of Deep Learning Models Using Synthetic Datasets

    Publikacja

    - Rok 2022

    In 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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  • System do prototypowania bezprzewodowych inteligentnych urządzeń monitoringu audio-video

    Publikacja

    - Rok 2013

    W komunikacie przedstawiono system prototypowania bezprzewodowych urządzeń do monitoringu audio-video. System bazuje na układach FPGA Virtex6 i wielu dodatkowych wspierających urządzeniach jak: szybka pamięć DDR3, mała kamera HD, mikrofon z konwerterem A/C, moduł radiowy WiFi, itp. Funkcjonalność systemu została szczegółowo opisana w komunikacie. System został zoptymalizowany do pracy pod kontrolą systemu operacyjnego Linux, zostały...

  • High-Speed Binary-to-Residue Converter Design Using 2-Bit Segmentation of the Input Word

    In 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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  • Design Elements of Affect Aware Video Games

    Publikacja

    - Rok 2015

    In this paper issues of design and development process of affect-aware video games are presented. Several important design aspects of such games are pointed out. A concept of a middleware framework is proposed that separates the development of affect-aware video games from emotion recognition algorithms and support from input sensors. Finally, two prototype affect-aware video games are presented that conform to the presented architecture...

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  • Weighted Clustering for Bees Detection on Video Images

    Publikacja

    This work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...

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  • Emotion Recognition for Affect Aware Video Games

    In this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented

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  • Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding

    Publikacja
    • Z. Waldman
    • L. Camarillo-Rodriguez
    • I. Chervenova
    • B. Berry
    • S. Shimamoto
    • B. Elahian
    • M. T. Kucewicz
    • C. Ganne
    • X. He
    • L. A. Davis... i 17 innych

    - EPILEPSY & BEHAVIOR - Rok 2018

    BACKGROUND: We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding. METHODS: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the...

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  • Environmental failure of dental biomaterials

    W pracy przedstawiono problematykę związaną z zagadnieniem trwałości biomateriałów stomatologicznych. Scharakteryzowano kryteria doboru materiałów i na przykładzie koron stomatologicznych pokazano wyniki oceny prawidłowości doboru w oparciu o metodę elementów skończonych. Przedstawiono wyniki weryfikacji doświadczalnej i wskazano na możliwości wykorzystania tej metody do konstruowania odpornych na zniszczenie koron metalowo-ceramicznych.

  • Deep Learning Basics 2023/24

    Kursy Online
    • K. Draszawka

    A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

  • Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech

    Publikacja
    • D. Korzekwa
    • R. Barra-Chicote
    • B. Kostek
    • T. Drugman
    • M. Łajszczak

    - Rok 2019

    We present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...

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  • Generalized Formulation of Response Features for Reliable Optimization of Antenna Input Characteristics

    Electromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models, are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure...

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  • Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms

    Publikacja

    - Rok 2014

    Implementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...

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  • e-Learning - user's guide for students

    Kursy Online

    e-Learning - user's guide for students

  • Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift

    While 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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  • Multi-Temporal Analysis of Changes of the Southern Part of the Baltic Sea Coast Using Aerial Remote Sensing Data

    Publikacja

    - Remote Sensing - Rok 2022

    Understanding processes that affect changes in the coastal zone and the ability to predict these processes in the future depends on the period for which detailed monitoring is carried out and on the type of coast. This paper analyzes a southern fragment of the Baltic coast (30 km), where there has been no anthropogenic impact (Slowinski National Park). The study was carried out covering a time interval of 65 years. Historic and...

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  • POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2011

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  • Updating a hospital building. A task for innovation design

    Publikacja

    - Rok 2012

    Refurbishment of a hospital, especially located in a historical building, is a task that goes far beyond a standard framework of architectural practice. A concept of modularity in the architecture of the late nineteenth and early twentieth century was only just to happen, building system installations and technical equipment appeared as the simplest solutions. Inscribing complex functional solutions into such a space is an interesting...

  • Nonlinear Modeling in Time Domain Numerical Analysis of Stringed Instrument Dynamics

    Publikacja

    Musical instruments are very various in terms of sound quality with their timbre shaped by materials and geometry. Materials' impact is commonly treated as dominant one by musicians, while it is unclear whether it is true or not. The research proposed in the study focuses on determining influence of both these factors on sound quality based on their impact on harmonic composition. Numerical approach has been chosen to allowed independent...

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  • Closed-loop stimulation of temporal cortex rescues functional networks and improves memory

    Publikacja
    • Y. Ezzyat
    • P. A. Wanda
    • D. F. Levy
    • A. Kadel
    • A. Aka
    • I. Pedisich
    • M. R. Sperling
    • A. Sharan
    • B. C. Lega
    • A. Burks... i 12 innych

    - Nature Communications - Rok 2018

    Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct...

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  • A new multi-process collaborative architecture for time series classification

    Publikacja

    - KNOWLEDGE-BASED SYSTEMS - Rok 2021

    Time series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...

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  • Parallel Computations of Text Similarities for Categorization Task

    Publikacja

    - Rok 2013

    In this chapter we describe the approach to parallel implementation of similarities in high dimensional spaces. The similarities computation have been used for textual data categorization. A test datasets we create from Wikipedia articles that with their hyper references formed a graph used in our experiments. The similarities based on Euclidean distance and Cosine measure have been used to process the data using k-means algorithm....

  • Urban scene semantic segmentation using the U-Net model

    Publikacja

    - Rok 2023

    Vision-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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  • Visual Features for Endoscopic Bleeding Detection

    Aims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...

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