Machine Learning Algorithms for Signal and Image Processing (Hardcover)

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.

本書以互動的實際應用案例，幫助讀者理解機器學習和深度學習技術的基本概念，並應用於信號和圖像處理領域。

《信號和圖像處理的機器學習算法》幫助讀者利用機器學習的進展來設計和開發現實世界應用，以增強和改進語音信號處理、圖像處理、計算機視覺、生物醫學信號處理、自適應濾波和文本處理等領域。書中介紹了應用於預處理、特徵提取、源分離或數據分解等信號處理技術，以實現機器學習任務。

本書由經驗豐富的作者撰寫，並由一個專家團隊共同貢獻，涵蓋了許多重要主題，包括：

- 語音識別、圖像重建、物體分類和檢測以及文本處理
- 醫療監測、生物醫學系統和綠色能源
- 各種機器學習和深度學習技術如何提高準確性、精確率、召回率和處理時間
- 實際應用和案例，包括智能手語識別、社交媒體中的假新聞檢測、結構損壞預測和癲癇發作檢測

對於希望進一步改進信號和圖像處理工作的專業人士，本書是一個易於理解但極為全面的參考資料。同時，對於相關領域的學生和研究人員來說，本書也是一個有價值的資源，可以深入了解該領域的歷史和最新發展。

Dr. Deepika Ghai is Assistant Professor of Signal and Image Processing at Lovely Professional University, India. Dr. Ghai received her PhD from Punjab Engineering College, India.

Dr. Suman Lata Tripathi is Professor of VLSI Design at Lovely Professional University, India. She is an IEEE senior member and received her PhD in microelectronics and VLSI from MNNIT, Allahabad.

Dr. Sobhit Saxena is Associate Professor at Lovely Professional University. He completed his PhD from IIT Roorkee in Nanomaterials.

Dr. Manash Chanda is Assistant Professor in the Department of ECE, Meghnad Saha Institute of Technology, India. He received his PhD in Engineering from Jadavpur University in 2018.

Dr. Mamoun Alazab is Associate Professor at the College of Engineering, IT and Environment at Charles Darwin University, Australia. He has published 150+ research papers in international journals and conferences, such as IEEE Transactions on Industrial Informatics

Dr. Deepika Ghai 是印度Lovely Professional University的信號和圖像處理助理教授。Dr. Ghai在印度旁遮普工程學院獲得了博士學位。

Dr. Suman Lata Tripathi 是印度Lovely Professional University的VLSI設計教授。她是IEEE的高級會員，並在MNNIT, Allahabad獲得了微電子和VLSI的博士學位。

Dr. Sobhit Saxena 是印度Lovely Professional University的副教授。他在IIT Roorkee完成了納米材料的博士學位。

Dr. Manash Chanda 是印度Meghnad Saha Institute of Technology的ECE系助理教授。他在2018年從Jadavpur University獲得了工程學博士學位。

Dr. Mamoun Alazab 是澳大利亞查爾斯達爾文大學工程、IT和環境學院的副教授。他在國際期刊和會議上發表了150多篇研究論文，如IEEE Transactions on Industrial Informatics。