Machine Learning Applications: From Computer Vision to Robotics

Practical resource the importance of Machine Learning and Deep Learning applications in various technologies and important real-world situations

New-Age Machine Learning Applications discusses methodological advancements of machine learning and deep learning, presents applications in image processing, including face and vehicle detection, image classification, object detection, image segmentation, and more, delivers real-world applications in healthcare to identify diseases and diagnosis, such as by creating smart health records and medical imaging diagnosis, and provides real-world examples, case studies, use cases, and techniques to enable the reader's active learning.

Composed of 13 chapters, this book also introduces real-world applications of machine and deep learning in blockchain technology, cyber security, and climate change. An explanation of AI and robotic applications in mechanical design is also discussed, including robot-assisted surgeries, security, and space exploration. The editors and contributors describe the importance of each subject area and detail why they are so important to us from a societal and human perspective.

Edited by two highly qualified academics and contributed to by established thought leaders in their respective fields, New-Age Machine Learning Applications includes information on:

• Content based medical image retrieval (CBMIR), covering face and vehicle detection, multi-resolution and multisource analysis, manifold and image processing, and morphological processing
• Smart medicine, including machine learning and artificial intelligence in medicine, risk identification, tailored interventions, and association rules
• Ai and robotics application for transportation and infrastructure (e.g., autonomous cars and smart cities), along with global warming and climate change
• Identifying diseases and diagnosis, drug discovery and manufacturing, medical imaging diagnosis, personalized medicine, and smart health records

With its practical approach to the subject, New-Age Machine Learning Applications is an ideal resource for professionals working with smart technologies such as machine and deep learning, AI, IoT, and other wireless communications; it is also highly suitable for professionals working in robotics, computer vision, cyber security and more.

《新時代機器學習應用》是一本實用的資源，介紹了機器學習和深度學習在各種技術和重要現實情境中的重要性。本書討論了機器學習和深度學習的方法論進展，介紹了圖像處理中的應用，包括人臉和車輛檢測、圖像分類、物體檢測、圖像分割等。同時，本書還提供了在醫療保健領域中的實際應用，例如創建智能健康記錄和醫學影像診斷，以及提供實際案例、案例研究、應用案例和技術，以促進讀者的主動學習。

本書共有13章，還介紹了機器學習和深度學習在區塊鏈技術、網絡安全和氣候變化等領域的實際應用。書中還討論了機器設計中人工智能和機器人應用的解釋，包括機器人輔助手術、安全和太空探索。編輯和貢獻者詳細描述了每個主題領域的重要性，並解釋了從社會和人類角度來看它們為什麼如此重要。

《新時代機器學習應用》由兩位高資歷的學者編輯，並由各自領域的知名思想領袖貢獻，其中包括以下內容:
- 基於內容的醫學影像檢索（CBMIR），包括人臉和車輛檢測、多分辨率和多源分析、流形和圖像處理、形態處理等。
- 智能醫學，包括機器學習和人工智能在醫學中的應用、風險識別、定制干預和關聯規則。
- 交通和基礎設施的人工智能和機器人應用（例如自動駕駛汽車和智能城市），以及全球變暖和氣候變化。
- 疾病識別和診斷、藥物發現和製造、醫學影像診斷、個性化醫學和智能健康記錄。

《新時代機器學習應用》以其實用的方法成為專業人士的理想資源，尤其適合從事機器學習、深度學習、人工智能、物聯網和其他無線通信等智能技術的專業人士；同時也非常適合從事機器人、計算機視覺、網絡安全等領域的專業人士。

Indranath Chatterjee is a Professor in the Department of Computer Engineering at Tongmyong University, South Korea. He received his PhD from University of Delhi, India and has authored several books and numerous research papers. His areas of research are AI, computer vision, computation neuroscience and medical imaging.

Sheetal Zalte is an Assistant Professor in the Department of Computer Science at Shivaji University, India. She earned her PhD from Shivaji University, India, and to date, she has published many research papers. Her research area is mobile adhoc network.

Indranath Chatterjee是韓國東明大學計算機工程系的教授。他在印度德里大學獲得博士學位，並撰寫了多本書籍和大量研究論文。他的研究領域包括人工智慧、計算機視覺、計算神經科學和醫學影像。

Sheetal Zalte是印度Shivaji大學計算機科學系的助理教授。她在Shivaji大學獲得博士學位，並發表了許多研究論文。她的研究領域是移動自組網路。