Pattern Recognition and Information Processing

15th International Conference, PRIP 2021, Minsk, Belarus, September 21–24, 2021, Revised Selected Papers

AvAlexander V. Tuzikov,Alexei M. Belotserkovsky

Häftad, Engelska, 2022

Del 1562 i serien Communications in Computer and Information Science

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Beskrivning

This book constitutes the refereed proceedings of the 15th International Conference on Pattern Recognition and Information Processing, PRIP 2021, held in Minsk, Belarus, in September 2021.

Produktinformation

Utgivningsdatum:2022-03-18
Mått:155 x 235 x 15 mm
Vikt:400 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:245
Förlag:Springer Nature Switzerland AG
ISBN:9783030988821

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Innehållsförteckning

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 Methodfor 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.