Explainable AI: Building Trustworthy Deep Learning Systems
暫譯: 可解釋的 AI：打造值得信賴的深度學習系統

Mala, D. Jeya, Ganesan, Subramaniam

Explainable AI: Building Trustworthy Deep Learning Systems
  • 出版商: CRC
  • 出版日期: 2026-10-28
  • 售價: $4,750
  • 貴賓價: 9.5 折 $4,512
  • 語言: 英文
  • 頁數: 188
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1041046871
  • ISBN-13: 9781041046875
  • 相關分類: DeepLearning、Machine Learning

    • 尚未上市，無法訂購

相關主題

商品描述

With the increasing use of deep learning systems across various industries, there is a growing need to make their decision-making processes more understandable and transparent. Regulatory requirements now demand clarity, and users and stakeholders want to know how AI systems work. The textbook addresses these needs by providing a detailed guide on integrating Explainable AI (XAI) into the Deep Learning Operations (DLOps) pipeline. By doing so, organizations can implement Continuous Integration (CI) and Continuous Deployment (CD) practices effectively.

Explainable AI: Building Trustworthy Deep Learning Systems focuses on how to incorporate XAI models, tools, and techniques to clarify machine learning decisions. It explores applications in fields such as healthcare, defense, human activity recognition, and object identification. The book offers practical advice on embedding XAI tools throughout the lifecycle of deep learning systems, covering topics like Explainability and Interpretability, Deep Learning Operations (DLOps), and Machine Learning Operations (MLOps). It also includes real-world examples, challenges, and solutions.

This textbook is ideal for undergraduate and graduate students studying computer science, electronic and communications engineering, and electrical and electronics engineering. It is particularly suited for courses like AI Internals in Cyber-Physical Systems, AI Security Analytics, and Human-Computer Interaction with XAI. Professionals in systems engineering and industrial engineering will also find it valuable.

For those adopting the textbook for courses, a solutions manual and PowerPoint slides are available.

商品描述(中文翻譯)

隨著深度學習系統日益廣泛地應用於各個產業，讓其決策過程更容易理解且更加透明的需求也隨之增加。現今的法規要求決策必須具備清晰度，而使用者與利害關係人也希望了解 AI 系統的運作方式。本教科書針對這些需求，提供將可解釋 AI（Explainable AI，XAI）整合至深度學習運維（Deep Learning Operations，DLOps）流程中的詳細指南。透過這種方式，組織便能有效實施持續整合（Continuous Integration，CI）與持續部署（Continuous Deployment，CD）實務。

《Explainable AI: Building Trustworthy Deep Learning Systems》聚焦於如何整合 XAI 模型、工具與技術，以釐清機器學習的決策過程。本書探討 XAI 在醫療保健、國防、人類活動辨識與物件識別等領域的應用，並提供在深度學習系統生命週期中導入 XAI 工具的實務建議，涵蓋可解釋性與可詮釋性（Explainability and Interpretability）、深度學習運維（Deep Learning Operations，DLOps）以及機器學習運維（Machine Learning Operations，MLOps）等主題。書中也收錄真實世界的案例、挑戰與解決方案。

本教科書適合修讀 computer science、電子與通訊工程，以及電機與電子工程的學士班與研究所學生。尤其適用於「Cyber-Physical Systems 中的 AI Internals」、「AI Security Analytics」以及「Human-Computer Interaction with XAI」等課程。系統工程與工業工程領域的專業人士也能從本書中獲益。

對於將本教科書採用於課程教學的讀者，另提供解答手冊與 PowerPoint 投影片。

作者簡介

Dr. D. Jeya Mala is currently a professor in the School of Computer Science and Engineering (SCOPE), Vellore
Institute of Technology, Chennai, Tamil Nadu, India. She has more than 24 years of teaching and research
experience and 4 years of industrial experience. As a member of the "National Work Group on Quantum
Computing" formed by the Telecommunications Department, Government of India, she contributed to
India's proposal on Quantum Computing for Future Networks at the Geneva Meet, Switzerland. She served
as an expert evaluation committee member of AICTENEAT, Government of India, and MoE's Innovation
Council, Government of India. To her research credit, she has one granted design patent, three published utility patents from IP, Government of India, one completed funded research project, 4 books, and more than 65 papers published in reputed refereed SCI- and Scopus-indexed journals, conferences, and book chapters. She is
currently working on a funded quantum-based collaborative research project with Deakin University, Australia. She is a listee of Who's Who list of SEBASE repository of University College London, UK, for her research work in the area of searchbased software engineering and a proud recipient of several laurels and awards, and member of IEEE, ACM, etc. Her research interests include artificial intelligence, quantum computing, DL and ML, XAI, healthcare analytics, software engineering, cybersecurity, and blockchain.

Dr. Subramaniam Ganesan, a professor in the Department of Electrical & Computer Engineering (ECE), Oakland University, Rochester, Michigan, USA. He is a senior member of IEEE, former IEEE Computer
Society Distinguished Visiting Speaker, IEEE Region for 4 Technical Activities member, and fellow of ISPE.
He has received the Lifetime Achievement Award from ISAM, the Lloyd L. Withrow Distinguished Speaker
Award from SAE, the Best Paper Award from ISAM, the Best Teacher Award from ASEE, and similar accolades from Oakland University. He is the editor-in-chief of the International Journal of Embedded Systems & Computer Engineering, as well as the International Journal of Sensors & Applications. He has been the session organizer of the "Systems Engineering" panel at the SAE World Congress for the past 15 years. More details can be viewed on the home page at: www.secs.oakland.edu/ ganesan. His research interests are in real-time systems, parallel architectures, mobile computing, automotive embedded systems, and signal processing. He holds several patents in embedded systems.
systems.Computing, Automotive Embedded Systems, and Signal Processing.

作者簡介(中文翻譯)

D. Jeya Mala 博士目前任教於印度泰米爾納德邦清奈的 Vellore Institute of Technology 電腦科學與工程學院（School of Computer Science and Engineering, SCOPE），擔任教授。她擁有超過 24 年的教學與研究經驗，以及 4 年的業界經驗。她是由印度政府電信部成立之「National Work Group on Quantum Computing」成員，並曾在瑞士日內瓦會議中，參與印度針對未來網路量子計算（Quantum Computing）的提案工作。她曾擔任印度政府 AICTE NEAT 專家評估委員會，以及印度政府教育部（MoE）Innovation Council 的成員。

在研究成果方面，她擁有 1 項已核准的設計專利、3 項由印度政府智慧財產相關機構（IP）公布的實用新型專利、1 項已完成的資助研究計畫、4 本著作，以及超過 65 篇發表於知名同儕審查 SCI 與 Scopus 索引期刊、會議及書籍章節中的論文。目前，她正與澳洲 Deakin University 合作進行一項受資助的量子計算研究計畫。由於在搜尋導向軟體工程（search-based software engineering）領域的研究成果，她獲列入英國 University College London SEBASE repository 的 Who’s Who 名錄。她也曾獲得多項榮譽與獎項，並為 IEEE、ACM 等組織的會員。她的研究興趣包括人工智慧、量子計算、深度學習（DL）與機器學習（ML）、可解釋人工智慧（XAI）、醫療分析、軟體工程、網路安全，以及區塊鏈。

Subramaniam Ganesan 博士是美國密西根州羅徹斯特 Oakland University 電機與電腦工程系（Department of Electrical & Computer Engineering, ECE）的教授。他是 IEEE 資深會員、前任 IEEE Computer Society Distinguished Visiting Speaker、IEEE Region 4 Technical Activities 委員，以及 ISPE Fellow。他曾獲得 ISAM 頒發的 Lifetime Achievement Award、SAE 頒發的 Lloyd L. Withrow Distinguished Speaker Award、ISAM 頒發的 Best Paper Award、ASEE 頒發的 Best Teacher Award，以及 Oakland University 頒發的其他類似榮譽。

他是 International Journal of Embedded Systems & Computer Engineering 以及 International Journal of Sensors & Applications 的總編輯。過去 15 年來，他一直擔任 SAE World Congress「Systems Engineering」論壇的議程主辦人。更多資訊請參閱其個人首頁：www.secs.oakland.edu/ganesan。他的研究興趣包括即時系統、平行架構、行動運算、汽車嵌入式系統，以及訊號處理。他在嵌入式系統領域擁有多項專利。

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