000			05576cam a2200505 i 4500
999			_c92561 _d92561
005			20250905100355.0
006			m o d
007			cr cnu---unuuu
008			250905s2024 njum ob u001 0 eng
020			_a9781394173358 _qelectronic book
020			_a1394173350 _qelectronic book
020			_a9781394173341 _qelectronic book
020			_a1394173342 _qelectronic book
020			_a1394173334 _qelectronic book
020			_a9781394173334 _q(electronic bk.)
020			_z9781394173327 _qhardcover
024	7		_a10.1002/9781394173358 _2doi
035			_a(OCoLC)1405845716
037			_a10368374 _bIEEE
040			_aDLC _beng _erda _cDLC _dOCLCF _dOCLCO _dYDX _dN$T _dDG1 _dIEEEE
041			_aeng
042			_apcc
050	0	4	_aQ325.5 _b.M321323 2024
082	0	0	_a006.3/1 _223/eng/20231023
245	0	0	_aMachine learning applications : _bfrom computer vision to robotics / _cedited by Indranath Chatterjee, Sheetal Zalte.
264		1	_aHoboken, New Jersey : _bWiley-IEEE Press, _c[2024]
300			_a1 online resource (xvi, 221 pages) : _billustrations (chiefly color)
336			_atext _btxt _2rdacontent.
337			_acomputer _bc _2rdamedia.
338			_aonline resource _bcr _2rdacarrier.
340			_2rdacc _0http://rdaregistry.info/termList/RDAColourContent/1003.
504			_aIncludes bibliographical references and index.
505	0		_aStatistical similarity in machine learning -- Development of machine learning-based methodologies for adaptive intelligent e-learning systems and time series analysis techniques -- Time-series forecasting for stock market using convolutional neural networks -- Comparative study for applicability of color histograms for CBIR used for crop leaf disease detection -- Stock Index Forecasting Using RNN-Long Short Term Memory -- Study and analysis of machine learning models for detection of phishing URLs -- Real-world applications of blockchain technology in internet of things -- Advanced persistent threat: Korean cyber security knack model impost and applicability -- Integration of Blockchain Technology and Internet of Things: Challenges and its Solutions -- Machine learning techniques for swot analysis of online education system -- Crop yield and soil moisture prediction using machine learning algorithms. -- Multi-rate signal processing in WSN for channel capacity and energy efficiency using machine learning. -- Introduction to mechanical design of AI-based robotic system.
520			_a"Machine learning (ML), and deep learning (DL) technologies are changing virtually every industry around the world. These technologies are increasingly being used in robotics and vehicle automation, and in businesses such as financial services, retail, manufacturing, healthcare, and life sciences. This book details the advances in these technologies and presents case studies on how they can be applied to different domains such as image processing, computer vision, robotics, and more. Comprised of 13 chapters, this book introduces real-world applications of machine and deep learning to healthcare, blockchain technology, cyber security, and climate change completed with case studies, solutions, and use cases for the reader's active learning. With a team of expert contributors, applications to image processing are examined, including medical imaging, pattern recognition, object detection, image segmentation, image transformation, morphological processing and more. An explanation of AI and robotic applications in mechanical design is also discussed including robot-assisted surgeries, security, and space exploration. Aimed at professionals and researchers alike, this book covers a range of important machine and deep learning applications. The editors and contributors describe the importance of each subject area and detail why they are so important to us"-- _cProvided by publisher.
545	0		_aAbout the Author Indranath Chatterjee is a Professor in the Department of Computer Engineering, at Tongmyong University, South Korea. He received his PhD from University of Delhi, India and has authored several books and numerous, research papers. His areas of research are AI, computer vision, computation neuroscience and medical imaging. Sheetal Zalte is an Assistant Professor in the Department of Computer Science at Shivaji University, India. She earned her PhD from Shivaji University, India, and has published many research papers. Her research area is mobile adhoc networks.
650		0	_aMachine learning _0https://id.loc.gov/authorities/subjects/sh85079324 _xIndustrial applications. _0https://id.loc.gov/authorities/subjects/sh00006117.
650		0	_aMachine learning _0https://id.loc.gov/authorities/subjects/sh85079324 _xScientific applications. _0https://id.loc.gov/authorities/subjects/sh2002007677.
650		0	_aDeep learning (Machine learning) _0https://id.loc.gov/authorities/subjects/sh2021006947 _xIndustrial applications. _0https://id.loc.gov/authorities/subjects/sh00006117.
650		0	_aDeep learning (Machine learning) _0https://id.loc.gov/authorities/subjects/sh2021006947 _xScientific applications. _0https://id.loc.gov/authorities/subjects/sh2002007677.
655		4	_aElectronic books.
700	1		_aChatterjee, Indranath, _0https://id.loc.gov/authorities/names/no2022111937 _eeditor.
700	1		_aZalte, Sheetal S., _0https://id.loc.gov/authorities/names/no2022111936 _eeditor.
856			_uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781394173358 _yFull text is available at Wiley Online Library Click here to view
942			_2ddc _cER