This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3.
The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.
本書提供了深度學習在影像分析應用方面的最先進覆蓋。書中展示了各種深度學習演算法，這些演算法能為各種與影像相關的問題提供實際解決方案；同時也說明了這些演算法如何被業界和學術界的科學家和學者所使用。內容包括自編碼器和深度卷積生成對抗網路在改善孟加拉手寫字符分類性能方面的應用，利用特徵選擇方法基於深度學習的方式自動診斷 COVID-19 疾病的 X 光影像，處理分類的不平衡影像數據集，使用深度轉移學習進行影像標題生成，開發車輛超速檢測系統，創建基於視頻的智能接近分析系統，利用深度學習建立黑色素瘤癌症檢測系統，使用 AlexNet 進行植物疾病分類，處理高光譜影像的深度學習，使用 EfficientNet 和 InceptionV3 進行肺炎疾病的胸部 X 光影像分類。
本書還探討了在計算時間和推理及建模不同類型數據的複雜性方面實施深度學習的困難。每一章都應用各種新的或現有的深度學習模型，如深度神經網路 (DNN) 和深度卷積神經網路 (DCNN)。書中詳細討論了在 MATLAB、Python 和 R 程式環境中可用的深度學習套件的使用，因此讀者也能了解深度學習的實際實施。本書的內容以簡單明瞭的風格呈現，適合對深度學習在影像分析應用研究領域感興趣的專業人士、非專業人士、科學家和學生。
Sanjiban Sekhar Roy is currently a Professor with the School of Computer Science and Engineering, Vellore Institute of Technology. He received Ph.D. degree from the Vellore Institute of Technology, Vellore, India, in 2016. He has edited handful of special issues for journals, published numerous articles in SCI high impact journals such as IEEE Transactions on Computational social systems; Scientific Reports, Nature; Computers and Electrical Engineering, Elsevier and many other reputed journals;Dr Roy has published nine books with reputed international publishers such as Springer, Elsevier and IGI Global. His research interests are deep learning and advanced machine learning.Dr. Roy was a recipient of the "Diploma of Excellence" Award for academic research from the Ministry of National Education, Romania. He was also an Associate Researcher with Ton Duc Thang University, Ho Chi Minh City, Vietnam, during 2019 to 2020.Ching-Hsien Hsu is Chair Professor of the College of Information and Electrical Engineering, Asia University, Taiwan; Professor in the department of Computer Science and Information Engineering, National Chung Cheng University; Research Consultant, Dept. of Medical Research, China Medical University Hospital, China Medical University, Taiwan. His research includes cloud and edge computing, big data analytics, high performance computing systems, parallel and distributed systems, artificial intelligence, medical AI and natural language processing. He has published 350+ papers in top journals such as IEEE TPDS, IEEE TSC, ACM TOMM, IEEE TCC, IEEE TETC, IEEE System, IEEE Network, top conferences, and book chapters in these areas. Dr. Hsu is the editor-in-chief of International Journal of Grid and High Performance Computing, and International Journal of Big Data Intelligence; and serving as editorial board for a number of prestigious journals, including IEEE Transactions on Service Computing, IEEE Transactions on Cloud Computing, International Journal of Cloud Computing, Journal of Communication Systems, International Journal of Computational Science, AutoSoft Journal. He has been acting as an author/co-author or an editor/co-editor of 10 books from Elsevier, Springer, IGI Global, World Scientific and McGraw-Hill. Dr. Hsu was awarded seven times talent awards from Ministry of Science and Technology, Ministry of Education, and nine times distinguished award for excellence in research from Chung Hua University, Taiwan. Prof. Hsu is president of Taiwan Association of Cloud Coputing; Chair of IEEE Technical Committee on Cloud Computing (TCCLD); Fellow of the IET (IEE) and senior member of the IEEE.
Venkateswara Rao Kagita is an Assistant Professor at NIT Warangal. He has obtained Ph.D from the University of Hyderabad. His research interests are Data Mining, Machine Learning, and Deep learning with a specific focus on machine learning techniques for recommender systems. His research works have been published in various reputed journals and conference proceedings. He has also delivered various guest lectures in several International and National workshops, IITs, NITs, and Universities.
Sanjiban Sekhar Roy 目前是維洛爾科技學院計算機科學與工程學院的教授。他於2016年獲得印度維洛爾科技學院的博士學位。他編輯了幾本期刊的特刊，並在多個高影響力的SCI期刊上發表了大量文章，如《IEEE計算社會系統學報》、《科學報告》、《自然》、《計算機與電氣工程》（Elsevier）及其他多本知名期刊。Roy博士與知名國際出版社如Springer、Elsevier和IGI Global出版了九本書籍。他的研究興趣包括深度學習和先進機器學習。Roy博士曾獲得羅馬尼亞國家教育部頒發的學術研究「卓越文憑獎」。他在2019至2020年間擔任越南胡志明市的董德長大學的副研究員。
許景賢教授是亞洲大學資訊與電機工程學院的講座教授；國立中正大學計算機科學與資訊工程系的教授；中國醫藥大學醫學研究部的研究顧問。他的研究領域包括雲端與邊緣計算、大數據分析、高效能計算系統、平行與分散式系統、人工智慧、醫療AI及自然語言處理。他在IEEE TPDS、IEEE TSC、ACM TOMM、IEEE TCC、IEEE TETC、IEEE System、IEEE Network等頂尖期刊及會議上發表了350篇以上的論文，並在這些領域的書籍章節中發表。許博士是《國際網格與高效能計算期刊》和《國際大數據智慧期刊》的主編，並擔任多本知名期刊的編輯委員會成員，包括《IEEE服務計算學報》、《IEEE雲計算學報》、《國際雲計算期刊》、《通訊系統學報》、《國際計算科學期刊》、《AutoSoft期刊》。他擔任過10本書籍的作者/合著者或編輯/共同編輯，這些書籍由Elsevier、Springer、IGI Global、World Scientific和McGraw-Hill出版。許博士曾七次獲得科技部、教育部的才華獎，並九次獲得中華大學的卓越研究獎。許教授是台灣雲計算協會的會長；IEEE雲計算技術委員會（TCCLD）的主席；IET（IEE）院士及IEEE的資深會員。
Venkateswara Rao Kagita 是NIT Warangal的助理教授。他獲得了海得拉巴大學的博士學位。他的研究興趣包括數據挖掘、機器學習和深度學習，特別專注於推薦系統的機器學習技術。他的研究成果已發表在多個知名期刊和會議論文集中。他還在多個國際和國內研討會、IIT、NIT及大學中進行了多場特邀演講。
