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Pattern recognition and information ...
PRIP (Conference) (2021 :)

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  • Pattern recognition and information processing = 15th International Conference, PRIP 2021, Minsk, Belarus, September 21-24, 2021 : revised selected papers /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Pattern recognition and information processing/ edited by Alexander V. Tuzikov, Alexei M. Belotserkovsky, Marina M. Lukashevich.
    其他題名: 15th International Conference, PRIP 2021, Minsk, Belarus, September 21-24, 2021 : revised selected papers /
    其他題名: PRIP 2021
    其他作者: Tuzikov, Alexander V.
    團體作者: PRIP (Conference)
    出版者: Cham :Springer International Publishing : : 2022.,
    面頁冊數: xii, 245 p. :ill. (some col.), digital ;24 cm.
    內容註: Retinal Image Analysis Approach for Diabetic Retinopathy Grading -- Mask R-CNN-based system for automated reindeer recognition and counting from aerial photographs -- Smart Tiling for Program Optimization and Parallelization -- Classification of Histology Images based on a Compact 3D Representation -- Authentication System Based on Biometric Data of Smiling Face from Stacked Autoencoder and Concatenated Reed-Solomon Codes -- Formalization of people and crowd detection and tracking for smart video surveillance -- Predicting events by analyzing the results of the work of predictive models -- Digest of Blockchain Technologies to Design System for Big Image Data Provenance and Security -- Generative Autoencoders for Designing Novel Small-Molecule Compounds As Potential Sars-COV-2 Main Protease Inhibitors -- Comparison of data preprocessing algorithms for nuclear segmentation in fluorescent immunohistology images of cancer cells -- A Bottom-up Method for Pose Detection of Multiple People on Real-Time Video -- Formalisation of Motion description in Microscopy Images -- 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 -- Simulation Modelling And Machine Learning Platforfm For Processing Fluorescence Spectroscopy Data -- Comparing the Performance of Classical and Deep Learning Methods on Small Image Datasets -- Investigation of the GAN-SSL Classifier Properties for Identification Expertise.
    Contained By: Springer Nature eBook
    標題: Pattern recognition systems - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-030-98883-8
    ISBN: 9783030988838
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