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Can I read Machine Learning Algorithms for Signal and Image Processing on EtoBox?

Machine Learning Algorithms for Signal and Image Processing by Tripathi, Suman Lata;Ghai, Deepika;Saxena, Sobhit;Chanda, Manash;Alazab, Mamoun; & Suman Lata Tripathi & Sobhit Saxena & Manash Chanda & Mamoun Alazab is a nonfiction available to read on EtoBox.

What is Machine Learning Algorithms for Signal and Image Processing about?

Machine Learning Algorithms for Signal and Image Processing 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 languag

Who reads Machine Learning Algorithms for Signal and Image Processing?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Tripathi, Suman Lata;Ghai, Deepika;Saxena, Sobhit;Chanda, Manash;Alazab, Mamoun; & Suman Lata Tripathi & Sobhit Saxena & Manash Chanda & Mamoun Alazab
Publisher
John Wiley & Sons, Incorporated
Published
2023
Language
EN
ISBN
9781119861836
Category
nonfiction
Subjects
Technology, Engineering, Computer Science

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