Machine learning algorithms for signal and image processing / edited by Deepika Ghai ... [et al.].
- 其他作者：
- 出版： Hoboken, N.J. :Piscataway, NJ : Wiley ;IEEE Press c2023.
- 主題： Signal processing--Digital techniques. , Image processing--Digital techniques. , Machine learning.
- ISBN： 9781119861829 (bound): NT4232 、 9781119861836 (adobe pdf) 、 9781119861843 (epub)
- 一般註：Includes bibliographical references and index.
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讀者標籤：
- 系統號： 000297219 | 機讀編目格式
館藏資訊
Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.
摘要註
"Machine Learning Algorithms for Signal and Image Processing aid the reader in designing and developing real-world applications of societal and industrial needs using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, text processing, etc. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. It will advance the current understanding of various machine and deep learning techniques in terms of their ability to improve upon the existing solutions with accuracy, precision rate, recall rate, processing time or otherwise. The most important is, it aims to bridge the gap among closely related fields of information processing including ML, DL, DSP, Statistics, Kernel Theory and others. It also aims to bridge the gap between academicians, researchers and industry to provide new technological solutions for healthcare, speech recognition, object detection and classification, etc. It will improve upon the current understanding about data collection and data preprocessing of signals and images for various applications, implementation of suitable machine and deep learning techniques for variety of signals and images, as well, possible collaboration to ensure successful design according to industry standards by working in a team. It will be helpful for researchers and designers to find out key parameters for future work in this area. The researchers working on machine and deep learning techniques can correlate their work with real-life applications of smart sign language recognition system, healthcare, smart blind reader system, text to image generation or vice-versa, etc. The book will be of interest to both beginners working in the field of machine and deep learning used for signal and image analysis, interdisciplinary in its nature"--
