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15th international conference on pattern recognition and information processing, prip 2021

ISBN: (纸本)9783030988821

the proceedings contain 17 papers. the special focus in this conference is on pattern recognition and information processing. the topics include: Retinal Image Analysis Approach for Diabetic Retinopathy Grading;comparison of Deep Learning Preprocessing Algorithms of Nuclei Segmentation on Fluorescence Immunohistology Images of Cancer Cells;simulation Modelling and Machine Learning Platform for processing Fluorescence Spectroscopy Data;a Bottom-Up Method for Pose Detection of Multiple People on Real-Time Video;authentication System Based on Biometric Data of Smiling Face from Stacked Autoencoder and Concatenated Reed-Solomon Codes;Detection of Features Regions of Syndrome in Multiple Sclerosis on MRI;automatic Tuning of the Motion Control System of a Mobile Robot Along a Trajectory Based on the Reinforcement Learning Method;smart Tiling for Program Optimization and Parallelization;digest of Blockchain Technologies to Design System for Big Image Data Provenance and Security;formalisation of Motion Description in Microscopy Images;predicting Events by Analyzing the Results of the Work of Predictive Models;formalization of People and Crowd Detection and Tracking for Smart Video Surveillance;Investigation of the GAN-SSL Classifier Properties for Identification Expertise;comparing the Performance of Classical and Deep Learning Methods on Small Image Datasets;Generative Autoencoders for Designing Novel Small-Molecule Compounds as Potential SARS-CoV-2 Main Protease Inhibitors.

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On Some Scientific Results of the 15th international conference prip-2021

On Some Scientific Results of the 15th International Confere...

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作者： Ablameyko, S.V. Gurevich, I.B. Krasnoproshin, V.V. Tuzikov, A. Yashina, V.V. Belarusian State University Minsk220030 Belarus Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow119333 Russia United Institute for Informatics Problems National Academy of Sciences of Belarus Minsk220012 Belarus

Abstract: the paper considers and analyzes the main scientific results of the 15th international conference on pattern recognition and information processing (prip-2021), Minsk, Republic of Belarus, September 2021. the history of this series of conferences is outlined and its significant role in the development of the theory and practice of image analysis, pattern recognition, and artificial intelligence is indicated. A list of articles in the special issue prepared on the basis of reports selected by the prip-2021 program committee is provided. © 2022, Pleiades Publishing, Ltd.

关键词： Image analysis

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PSD information based fatigue invariant hand gesture recognition using sEMG 15

PSD information based fatigue invariant hand gesture recogni...

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15th international conference on Signal processing and Communications (SPCOM)

作者： Dadape, Vedang Deshmukh, Arnav Sharma, Shivam Sharma, Rishi Raj Pimpri Chinchwad Coll Engn Dept Informat Technol Pune Maharashtra India Def Inst Adv Technol Dept Elect Engn Pune Maharashtra India

ISBN: (纸本)9798350350463;9798350350456

Surface electromyography (sEMG)-based hand gesture recognition (HGR) is crucial for pattern identification in today's society. Muscle fatigue presents a major challenge in sEMG signal analysis which affects the reliability of sEMG-based systems. this paper proposes a method for fatigue invariant HGR using sEMG signals. An onset-offset detection method is used to remove rest state from the signal, followed by extraction of power spectral density (PSD) information and various features for classification process. the model is trained on non-fatigue data and tested with multiple fatigue levels. It is noticed that accuracy decreases with increasing levels of fatigue for most of the cases. Comparative performance has been performed for various classifiers. the random forest (RF) classifier has achieved the better performance with accuracy (ACC), precision (PRE), recall (REC), and F1-score (F1) of 96.81%, 96.85%, 96.81%, and 96.81%, respectively.

关键词： Gesture recognition

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A Bottom-Up Method for Pose Detection of Multiple People on Real-Time Video 1

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15th international conference on pattern recognition and information processing, prip 2021

作者： Leunikau, Aliaksandr Nedzved, Alexander Belotserkovsky, Alexei Sholtanyuk, Stanislav Minsk Belarus Faculty of Applied Mathematics and Computer Science Belarusian State University Minsk Belarus Department of Intelligent Information Systems United Institute of Informatics Problems of NAS Belarus Minsk Belarus Belarusian State University Minsk Belarus

ISBN: (数字)9783030988838

ISBN: (纸本)9783030988821

关键词： Image recognition

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On Some Scientific Results of the 15th international conference prip-2021

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pattern recognition AND IMAGE ANALYSIS 2022年第2期32卷 249-253页

作者： Ablameyko, S. V. Gurevich, I. B. Krasnoproshin, V. V. Tuzikov, A. Yashina, V. V. Belarusian State Univ Minsk 220030 BELARUS Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow 119333 Russia Natl Acad Sci Belarus United Inst Informat Problems Minsk BELARUS

the paper considers and analyzes the main scientific results of the 15th international conference on pattern recognition and information processing (prip-2021), Minsk, Republic of Belarus, September 2021. the history of this series of conferences is outlined and its significant role in the development of the theory and practice of image analysis, pattern recognition, and artificial intelligence is indicated. A list of articles in the special issue prepared on the basis of reports selected by the prip-2021 program committee is provided.

关键词： prip-2021 image analysis pattern recognition artificial intelligence information processing

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Attention-guided Unsupervised Semantic Fusion for Infrared and Visible Images 15

Attention-guided Unsupervised Semantic Fusion for Infrared a...

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15th international conference on Graphics and Image processing, ICGIP 2023

作者： Qi, Qian Kong, Quan Liao, Qing Hu, Ziming Li, Jinglei Zhang, Jialian Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology University China School of Art & Design Wuhan Institute of Technology University China

ISBN: (纸本)9781510675018

Infrared and visible image fusion aims to synthesize a new image with complementary information of the source images such as the thermal radiation information and detailed texture information. However, the existing methods applied in the image fusion tasks tend to pay more attention to the improvements of visual quality and multiple evaluation indicators, while ignoring the importance of semantic information in high-level missions of image processing. In this paper, we present a novel approach to image fusion, where the synthesis of fused images is achieved through the utilization of semantic layouts generated via unsupervised learning. With the introduction of Attention Mechanism, the relationships between each pair of pixel points are gained to construct soft semantic layouts and further capture the global context information to make the same kind of semantics show the same fusion effect. By leveraging the semantic information, our method enables the automatic learning of fusion weights for two source images at the same spatial position. In comparison with other state-of-the-art image fusion methods, our experimental results obtained excellent performance both on qualitative results and quantitative indicators. Moreover, our method retains the high-level semantic information to the greatest extent, which is one of our outstanding characteristics. © 2024 SPIE. All rights reserved.

关键词： Image fusion

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Signal processing using Phase Diagram Analysis - New Perspectives in Understanding Transient Features in Data Science 15

Signal Processing using Phase Diagram Analysis - New Perspec...

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15th international conference on Communications, COMM 2024

作者： Ioana, Cornel Stanescu, Denis Nastasiu, Dragos Despina, Cristina Digulescu, Angela Université Grenoble-Alpes Gipsa-Lab Grenoble France ALTRANS Energies Grenoble France Military Technical Academy 'Ferdinand I' Telecommunications And Information Technology Department Bucharest Romania

ISBN: (纸本)9798350355956

In today's digital era, advancements in communications, artificial intelligence and big data are present in both professional and personal spheres, with data science playing a pivotal role in processing and decision-making across various domains such as multimedia, engineering and finance. Among the diverse data analysis techniques, transient phenomena analysis is crucial for understanding process variations and informing decisions. Traditional approaches to transient analysis include energy-based and model-based techniques. However, phase diagram analysis, originally used in dynamical systems, has emerged as a potent tool for uncovering transient features in signal processing. this method graphically represents system state trajectories over time, making transient features like sudden changes and anomalies more discernible. Its versatility is evident across multiple fields: in wireless communications for signal characterization and modulation recognition;in the energy sector for predictive maintenance of power grids, detecting early degradation and assessing risks;and in high-frequency and thz domains for enhancing imaging and sensing technologies by improving resolution and sensitivity. thus, phase diagram analysis significantly contributes to advancements in communication, energy management and high-frequency technology. © 2024 IEEE.

关键词： Transient analysis

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Forecasting the Impact of Deep Learning on Data Science Practices: A Comprehensive Analysis 15

Forecasting the Impact of Deep Learning on Data Science Prac...

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15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Acharjya, Kalyan Devaraj Verma, C. Umamaheswari, B. Shelke, Priya M. Kumar, Mukesh Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Ramnagar District562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Technology Department of Information Technology Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India

ISBN: (纸本)9798350370249

It comprehensively discusses the effect of deep mastering on data technology practices. Deep studying has advanced to become a powerful tool for information mining, pattern recognition, and feature engineering. It is miles information scientists are increasingly using the accuracy and efficiency of information science initiatives. Furthermore, the era has stepped forward hastily to one of these excessive levels. Many leading facts scientists throughout numerous domains have begun to contain deep mastering into their facts technological know-how workflows. In this paper, we examine and forecast the modern-day and destiny impact of deep gaining knowledge of data technology practices. We start by analyzing the distinct advantages of deep learning, including progressed accuracy, reduced guide attempt, more suitable automation, and advanced scalability. We then become aware of extraordinary applications in which deep learning is being applied and evaluate its impact on the respective information science pipelines. Sooner or later, we provide a comprehensive forecast of the capability applications of deep getting to know within the records technology subject inside the near and far destiny. Notably, we recall the capacity of deep studying to force essential modifications in how information mining, analytical choice-making, and large records packages. through our analysis, we will forecast the ability of deep studying to revolutionize statistics technological know-how practices in extraordinary ways. © 2024 IEEE.

关键词： Automation Practices processing Technology Unprecedented

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A Comparative Analysis of Texture Analysis Methods for Image Retrieval 15

A Comparative Analysis of Texture Analysis Methods for Image...

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15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dhabliya, Dharmesh Vijayalakshmi, V.J. Sharma, Amit Kumar Sood, Gourav Latha, B. Meena, Y.R. Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Teerthanker Mahaveer University College of Engineering Uttar Pradesh Moradabad India Chitkara University Institute of Engineering and Technology Centre for Interdisciplinary Research for Business and Technology punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai India School of Engineering and Technology Department of Civil Engineering Karnataka Bangalore India

ISBN: (纸本)9798350370249

Texture evaluation is a middle aspect of many computer vision obligations, consisting of pattern c, object recognition, and photogrammetry. this paper specializes in a comparative evaluation of popular texture analysis techniques utilized in photograph retrieval. 4 primary strategies are discussed here: local Binary patterns (LBP), Histogram of orientated Gradients (HOG), Scale Invariant feature transform (SIFT), and shape Tensor (ST). Each of those strategies quantifies a few details of the picture and converts it right into a characteristic vector. LBP is an easy and broadly used algorithm that computes an image's gray-scale depth. It utilizes a round community around every pixel to construct a texture descriptor. HOG is an extension of LBP that computes distortions in neighborhood gray-scale versions and orientations. SIFT extracts greater texture info than LBP or HOG by looking at variations between adjoining pixels. A structure tensor is an image-processing approach that computes 2D-order statistical moments to generate function vectors. the paper examines the performance of these techniques for numerous forms of texture distributions. It discovered that SIFT and ST executed pleasant basic. But, depending at the sort of software, a few methods are probably greater suitable than others. © 2024 IEEE.

关键词： Characteristic Evaluation Obligations Photogrammetry Popularity Variations

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Integrated Intelligent System for Scientific and Educational information Retrieval 15

Integrated Intelligent System for Scientific and Educational...

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15th international Scientific and Practical conference on Environment. Technology. Resources, ETR 2024

作者： Musaev, Mukhammadjon Rakhmatullaev, Marat Normatov, Sherbek Shukurov, Kamoliddin Abdullaeva, Malika Tashkent University of Information Technologies Named after Muhammad al-Khwarizmi Tashkent Uzbekistan Library Information Systems Tashkent University of Information Technologies Named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781713899570

the relevance of creating information systems using artificial intelligence methods and tools is dictated by the following reasons: the volume of scientific and educational information is growing;Traditional information retrieval methods have exhausted themselves. Using only deterministic and iteration methods, rigid algorithms don't give the expected results. they require more time to process information and more memory. Significant progress in recent years in the development of artificial intelligence (AI) methods and systems gives hope that their use will significantly reduce the time needed to search for data for scientific research and educational activities. the aim of the research results presented in the article is to increase the efficiency for scientific and educational information retrieval based on the use of AI methods implemented in the integrated intelligent information system "SMART TUIT". the article presents the results of theoretical and applied research obtained by several departments of the Tashkent University of information Technology (TUIT) in solving the following tasks: Voice recognition for subsequent processing;pattern recognition in order to identify the users of information;Search and processing of scientific and educational resources in electronic libraries;Analysis of information needs of users depending on the level of competence and type of activity;Evaluation of scientific and educational information to identify the most important data sources;Geoinformation system to solve the problems of the location of the information source. Initially, each research area in the departments was aimed at solving a certain class of problems related to medicine, linguistics, electronic libraries, corporate networks, information security systems, etc. the TUIT creative group decided to combine efforts to apply the results obtained to solve the important problem of intellectualizing the search for sources of scientific and educational information amon

关键词： Search engines

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