Machine Learning in Image Analysis and Pattern Recognition

doi:10.3390/books978-3-0365-1713-1

Download Url(s)

https://mdpi.com/books/pdfview/book/4232

Contributor(s)

Kumar, Munish (editor)

Sharma, R. K. (editor)

Sethi, Ishwar (editor)

Language

English

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Abstract

This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

URI

https://directory.doabooks.org/handle/20.500.12854/76783

Keywords

machine learning; deep learning; image processing; classification; tea; fermentation; automated image coding; data collection methods; interdisciplinary learning theory; research methods; systematic literature review; visitor use management; image classification; multi-instance learning; divergence; dissimilarity; bag-to-class; Kullback–Leibler; segment-based temporal modeling; two-stream network; action recognition; internet of things; detection; dataset; plant disease recognition; image segmentation; aphid; Aphoidea; lemon; breast cancer mammogram dataset; ultrasound breast cancer scans; BI-RADS; clinical data