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Machine Learning in Image Analysis and Pattern Recognition
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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.
This book is included in DOAB.
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Keywords
- action recognition
- aphid
- Aphoidea
- automated image coding
- bag-to-class
- BI-RADS
- breast cancer mammogram dataset
- Classification
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- data collection methods
- dataset
- deep learning
- Detection
- dissimilarity
- divergence
- Economics, finance, business & management
- Fermentation
- image classification
- Image processing
- image segmentation
- Industry & industrial studies
- Information technology industries
- interdisciplinary learning theory
- Internet of Things
- Kullback–Leibler
- lemon
- Machine learning
- Media, information & communication industries
- multi-instance learning
- plant disease recognition
- Research methods
- segment-based temporal modeling
- Systematic Literature Review
- Tea
- two-stream network
- ultrasound breast cancer scans
- visitor use management
Links
DOI: 10.3390/books978-3-0365-1713-1Editions