Wyniki wyszukiwania dla: IMAGE CLASSIFICATION IN VIDEOS - MOST Wiedzy

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Wyniki wyszukiwania dla: IMAGE CLASSIFICATION IN VIDEOS

Wyniki wyszukiwania dla: IMAGE CLASSIFICATION IN VIDEOS

  • Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2019

    This work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...

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  • Marta Kuc-Czarnecka dr

    Marta 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...

  • BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES

    In this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...

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  • Improving automatic surveillance by sound analysis

    Publikacja

    An automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...

  • Predicting emotion from color present in images and video excerpts by machine learning

    Publikacja

    This work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...

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  • Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics

    Publikacja

    - Rok 2020

    Remote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...

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  • Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach

    Publikacja

    - ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE - Rok 2023

    Ship imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...

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  • Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach

    Publikacja

    Breast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...

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  • Explainable machine learning for diffraction patterns

    Publikacja
    • S. Nawaz
    • V. Rahmani
    • D. Pennicard
    • S. P. R. Setty
    • B. Klaudel
    • H. Graafsma

    - Journal of Applied Crystallography - Rok 2023

    Serial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...

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  • Economical methods for measuring road surface roughness

    Two 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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  • Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks

    Deep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...

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  • Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images

    Publikacja

    - Remote Sensing - Rok 2022

    In 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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  • Deep convolutional neural network for predicting kidney tumour malignancy 

    Publikacja

    - Rok 2021

    Purpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...

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  • Behavior Analysis and Dynamic Crowd Management in Video Surveillance System

    A concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...

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  • Deep Features Class Activation Map for Thermal Face Detection and Tracking

    Publikacja

    - Rok 2017

    Recently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...

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  • Badanie stanu nawierzchni drogowej z wykorzystaniem uczenia maszynowego

    W artykule opisano budowę systemu informowania o stanie nawierzchni drogowej z wykorzystaniem metod cyfrowego przetwarzania obrazów oraz uczenia maszynowego. Efektem wykonanych prac badawczych jest eksperymentalna platforma, pozwalająca na rejestrację uszkodzeń na drogach, system do analizy, przetwarzania i klasyfikacji danych oraz webowa aplikacja użytkownika do przeglądu stanu nawierzchni w wybranej lokalizacji.

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  • Playback detection using machine learning with spectrogram features approach

    Publikacja

    This paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...

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  • Distributed Framework for Visual Event Detection in Parking Lot Area

    The paper presents the framework for automatic detection of various events occurring in a parking lot basing on multiple camera video analysis. The framework is massively distributed, both in the logical and physical sense. It consists of several entities called node stations that use XMPP protocol for internal communication and SRTP protocol with Jingle extension for video streaming. Recognized events include detecting parking...

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  • Seafloor Characterisation Using Underwater Acoustic Devices

    The problem of seafloor characterisation is important in the context of management as well as investigation and protection of the marine environment. In the first part of the paper, a review of underwater acoustic technology and methodology used in seafloor characterisation is presented. It consists of the techniques based on the use of singlebeam echosounders and seismic sources, along with those developed for the use of sidescan...

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  • Image Processing in Robotics (2021/2022)

    Kursy Online
    • P. Chudziak

    For ISD M.Sc. (II degr.) 2 sem. Participants are to learn image processing algorithms related to transformation, filtration, feature detection (image descriptors), image processing algorithms in robotic industrial systems.

  • Video content analysis in the urban area telemonitoring system

    Publikacja

    The 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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  • Seafloor Characterisation and Imaging Using Multibeam Sonar Data

    Publikacja

    The approach to seafloor characterisation and imaging is presented. It relies on the combined, concurrent use of several techniques of multibeam sonar data processing. The first one is based on constructing the grey-level sonar images of seabed using the backscattering strength calculated for the echoes received in the consecutive beams. Then, the set of parameters describing the local region of sonar image is calculated. The second...

  • Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy

    Publikacja

    - Rok 2018

    The diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...

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  • Journal of Classification

    Czasopisma

    ISSN: 0176-4268 , eISSN: 1432-1343

  • DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES

    Malignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...

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  • Melanoma skin cancer detection using mask-RCNN with modified GRU model

    Publikacja

    - Frontiers in Physiology - Rok 2024

    Introduction: 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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  • Image Processing in Robotics

    Kursy Online
    • T. Białaszewski

  • Image Processing in Robotics

    Kursy Online
    • S. Dziedziewicz

  • 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...

  • The effect of impacted third molars on second molar external root resorption, a cross-sectional cone beam computed tomography study

    Publikacja
    • G. Gürses
    • A. Akçakaya
    • A. Aktı
    • O. Aydin

    - Medicina Oral Patologia Oral y Cirugia Bucal - Rok 2023

    Background: Third molars have the highest prevalence of impaction in teeth and can cause pathological damage on the adjacent second molars. This study aims to evaluate the effects of factors related to impacted third molars on external root resorption (ERR) in adjacent second molars using cone-beam computed tomography (CBCT). Material and Methods: In CBCTs, the effect of impacted third molars on the root surface of adjacent second...

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  • Physics augmented classification of fNIRS signals

    Publikacja
    • F. Orihuela-Espina
    • M. Rojas-Cisneros
    • S. A. Montero-Hernández
    • J. S. Garcia Salinas
    • B. Cuervo-Soto
    • J. Herrera-Vega

    - Rok 2022

    Background. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...

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  • Cataloging & Classification Quarterly

    Czasopisma

    ISSN: 0163-9374 , eISSN: 1544-4554

  • Vegetation Classification and Survey

    Czasopisma

    eISSN: 2683-0671

  • On cooperative image denoising

    Publikacja

    - Rok 2011

    In this paper we suggest how several competing image denoising algorithms, differing in design parameters, or even in design principles, can be combined together to yield a better and more reliable denoising algorithm. The proposed fusion mechanism allows one to combine practically all kinds of noise reduction tools. It also allows one to account for the distribution of measurement noise, and in particular - to cope with heavy-tailed...

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  • The Courts Public image - The Desired Direction of Change

    Publikacja

    This paper proposes to scientifically explore notions of court identity, principles of shaping a court system's image, and best practices in positive court image development relating to thhe courts in Poland

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  • LEGO bricks for training classification network

    Dane Badawcze
    wersja 1.1 open access - seria: LEGO

    The data set contains images of 447 different classes of LEGO bricks used for training LEGO bricks classification network. The dataset contains two types of images: photos (10%) and renders (90%) aggregated into respective directories. Each directory (photos and renders) contains 447 directories labeled as the official brick type number. The images...

  • Image simulation and annotation for color blinded

    In this paper methods for image simulation as seen by a color blinded and a method for constructing images of perceived color difference are presented. The work is also focused on the interactive color description of an image contents. As a result, the individuals having problems with color discrimination can identify colors in an image.W artykule prezentowane są metody symulacji kolorów w obrazach postrzeganych przez osoby ze...

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  • Seabed classification using multibeam echosounder

    Publikacja

    The method of seabed identification and classification from multibeam sonar echoes is presented. The proposed approach is based on calculation of a set of parameters of an echo envelope, similarly as in seafloor classification using single beam echosounder. These parameters are extracted for each consecutive beam allowing the estimation of their dependence on the seafloor incident angle. The relation between seabed type and calculated...

  • Comparison of selected electroencephalographic signal classification methods

    A variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...

  • Impact of optimization of ALS point cloud on classification

    Airborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...

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  • Stereo image visualization for a VISROBOT system

    Publikacja

    - Rok 2013

    The article describes a novel approach to robotic vision in mobile robot systems. The system implements a Visrobot system which implements a generic idea of using mobile robots for exploring an indoor environment. The task of such a robot is to visualize a stereo image properly for an operator. The system uses different stereo baseline values. Variable baseline can result in increasing depth resolution for distant objects. We assume...

  • A System for Heart Sounds Classification

    The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...

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  • Overhead wires detection by FPGA real-time image processing

    Publikacja

    The paper presents design and hardware implementation of real-time image filtering for overhead wires detection divided on image processing and results presentation blocks. The image processing block was separated from the whole implementation, and its delay and hardware complexity was analysed. Also the maximum frequency of image processing of the proposed implementation was estimated.

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  • Using similar classification tasks in feature extractor learning

    Publikacja

    - Rok 2009

    The article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.

  • The parallel environment for endoscopic image analysis

    Publikacja

    - Rok 2002

    The jPVM-oriented environment to support high performance computing required for the Endoscopy Recommender System (ERS) is defined. SPMD model of image matching is considered and its two implementations are proposed: Lexicographical Searching Algorithm (LSA) and Gradient Serching Algorithm (GSA). Three classes of experiments are considered and the relative degree of similarity and execution time of each algorithm are analysed....

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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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  • An Objective Focussing Measure for Acoustically Obtained Image

    Publikacja

    In scientific literature many parameters of an image sharpness can be defined, that can be used for the evaluation of display energy concentration (EC). This paper proposes a new, simple approach to EC quantitative evaluation in spectrograms, which are used for the analysis and visualization of sonar signals. The presented approach of the global-image EC measure was developed to the evaluation of EC in arbitrary direction (or at...

  • Using multibeam echoes in seafloor characterisation and classification

    Publikacja

    The method of seabed identification and classification from multibeam sonar echoes is presented. The proposed approach is based on calculation of a set of parameters of an echo envelope, similarly as in seafloor classification using single beam echosounder. These parameters are extracted for each consecutive beam allowing the estimation of their dependence on the seafloor incident angle. The relation between seabed type and calculated...

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  • Driving the Image of an Electricity Supplier through Marketing Activities

    Publikacja

    - Forum Scientiae Oeconomia - Rok 2023

    The aim of this study is to determine how marketing actions undertaken within the marketing mix by electricity providers influence their image. Referring to the Stimulus-Organism-Response (SOR) theory, research hypotheses were formulated, and a regression model was constructed, assuming positive impacts of selected marketing actions of electricity providers on their image. A quantitative approach was employed to test the research...

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  • Reconstruction of 3D image of corona discharge streamer

    Publikacja
    • M. Kocik
    • M. Tański
    • J. Mizeraczyk
    • R. Ichiki
    • S. Kanazawa
    • J. Dembski

    - Rok 2010

    In this paper, the method of reconstruction of the 3D structure of streamers in DC positive corona discharge in nozzle-to-plate electrode configuration is presented. For reconstructing of 3D image of corona discharge streamer we propose a stereographical method, where streamers are observed from several directions simultaneously. The multi-directional observation enabled to obtain fine positional coordinates of streamers for a...

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