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008			221226s2023 si | o |1|| 0|eng d
020			_a9789811971693
024	7		_a10.1007/978-981-19-7169-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aHC79 .E5 _b2023 EB
245	0	0	_aComputer Vision and Machine Intelligence Paradigms for SDGs : _bSelect Proceedings of ICRTAC-CVMIP 2021 _cedited by R. Jagadeesh Kannan, Sabu M. Thampi, Shyh-Hau Wang
250			_a1st ed 2023
264		1	_aSingapore _bSpringer Nature _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aLecture Notes in Electrical Engineering _x1876-1119 _v967
505	0		_aPTZ-camera-based facial expression analysis using faster R-CNN for student engagement recognition -- Convergence Perceptual Model for Computing Time-Series-Data on Fog-Environment -- Localized Super Resolution for Foreground Images using U-Net and MR-CNN -- SMS Spam Classification Using PSO-C4.5 -- Automated Sorting, Grading of Fruits Based on Internal and External Quality Assessment Using HSI, Deep CNN -- Pest Detection using Improvised YOLO Architecture -- Classification of Fungi Effected Psidium Guajava Leaves using ML and DL Techniques -- Deep Learning Based Recognition of Plant Diseases -- Artificial Cognition of Temporal Events using Recurrent Point Process Networks -- On the Performance of Energy Efficient Video Transmission over LEACH based protocol in WSN -- Hybridization of Texture Features for Identification of Bi-lingual Scripts from Camera Images at Wordlevel -- Advanced Algorithmic Techniques for Topic Prediction and Recommendation - An Analysis -- Implementation of an automatic EEG feature extraction with Gated Recurrent Neural Network for Emotion Recognition.
520			_aThis book constitutes refereed proceedings of the 4th International Conference on Recent Trends in Advanced Computing - Computer Vision and Machine Intelligence Paradigms for Sustainable Development Goals. This book covers novel and state-of-the-art methods in computer vision coupled with intelligent techniques including machine learning, deep learning, and soft computing techniques. The contents of this book will be useful to researchers from industry and academia. This book includes contemporary innovations, trends, and concerns in computer vision with recommended solutions to real-world problems adhering to sustainable development from researchers across industry and academia. This book serves as a valuable reference resource for academics and researchers across the globe.
988			_aSpringer_Computer_2023
650		7	_2embne _9405551 _aDesarrollo sostenible _vCongresos y asambleas
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-7169-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _eb _zSI