000			02510nam a2200373 i 4500
999			_c397929 _d397929 _x1
001			397929
003			ES-MaUEC
005			20240314174450.0
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007			cr nn 008mamaa
008			221231s2023 si | o |||| 0|eng d
020			_a9789811958687
024	7		_a10.1007/978-981-19-5868-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1632 _b2023 EB
245	0	0	_aMachine Learning, Image Processing, Network Security and Data Sciences : _bSelect Proceedings of 3rd International Conference on MIND 2021 _cedited by Rajesh Doriya, Badal Soni, Anupam Shukla, Xiao-Zhi Gao
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 _v946
505	0		_aA Methodological review of Time Series Forecasting with Deep Learning Model : A Case study on Electricity Load and Price Prediction -- A Robust Secure Access Entrance Method Based on Multi Model Biometric Credentials Iris and Finger Print -- Prostate Cancer Grading using Multistage Deep Neural Networks.
520			_aThis book constitutes the refereed proceedings of the Third International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2021. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cybersecurity. This book aims to develop an understanding of image processing, networks, and data modeling by using various machine learning algorithms for a wide range of real-world applications. In addition to providing basic principles of data processing, this book teaches standard models and algorithms for data and image analysis. .
988			_aSpringer_Computer_2023
650		7	_2embne _9413188 _aProceso digital de imágenes _vCongresos y asambleas
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-5868-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _eb _zSI