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- Leidėjas: Apple Academic Press Inc.
- Metai: 2026
- Puslapiai: 269
- ISBN-10: 1779640765
- ISBN-13: 9781779640765
- Kalba: Anglų
Intelligent Computing and Analytics in Image Processing (el. knyga) (skaityta knyga) | knygos.lt
Atsiliepimai
Aprašymas
This new book, Intelligent Computing and Analytics in Image Processing, explores the amalgamation of intelligent computing, analytics, and image processing, introducing novel applications of smart technologies in image processing and presenting new solutions to image processing challenges.
The volume discusses the processing of biological and biomedical imaging, looking at machine learning and deep learning for diagnosis and detection of brain tumors, diabetes, pneumonia, heart disease, etc., in humans. The chapters also look at other applications of intelligent computing and machine learning in image processing, such as for detecting plant type and leaf disease, classifying and counting fruit, for forensics analysis, for face detection emotion, for sketch-to-photo synthesis, and more. Deep learning techniques such as convolutional neural network (CNN) and inception v3 contrast limited adaptive histogram equalization (CLAHE) and others are also discussed in detail.
Covering myriad advanced applications of intelligent technologies in image processing in diverse areas, this volume will valuable to researchers as well as professionals and students from various fields involved in intelligent computing and image processing.
- Leidėjas: Apple Academic Press Inc.
- Metai: 2026
- Puslapiai: 269
- ISBN-10: 1779640765
- ISBN-13: 9781779640765
- Kalba: Anglų
This new book, Intelligent Computing and Analytics in Image Processing, explores the amalgamation of intelligent computing, analytics, and image processing, introducing novel applications of smart technologies in image processing and presenting new solutions to image processing challenges.
The volume discusses the processing of biological and biomedical imaging, looking at machine learning and deep learning for diagnosis and detection of brain tumors, diabetes, pneumonia, heart disease, etc., in humans. The chapters also look at other applications of intelligent computing and machine learning in image processing, such as for detecting plant type and leaf disease, classifying and counting fruit, for forensics analysis, for face detection emotion, for sketch-to-photo synthesis, and more. Deep learning techniques such as convolutional neural network (CNN) and inception v3 contrast limited adaptive histogram equalization (CLAHE) and others are also discussed in detail.
Covering myriad advanced applications of intelligent technologies in image processing in diverse areas, this volume will valuable to researchers as well as professionals and students from various fields involved in intelligent computing and image processing.
Atsiliepimai