Explainable Machine Learning Models and Architectures

Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine learning models. Many real-time applications like processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems to have a lot of scope for improvements in terms of accuracy, speed, computational powers and overall power consumption.

This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must have for any library.

機器學習和深度學習模組現在已成為許多智能和自動化系統的重要組成部分，這些系統在不同層次上進行信號處理。以文本、圖像或視頻形式的信號處理需要以所需的數據速率和準確性進行大量的計算操作。大量數據需要更多使用嵌入式大容量記憶體的集成電路（IC）面積，進一步導致更多的IC面積。功耗、延遲和IC面積之間的權衡一直是設計師和研究人員關注的問題。需要新的硬體架構和加速器來探索和實驗高效的機器學習模型。許多實時應用，如醫療保健中的生物醫學數據處理、智能交通、衛星圖像分析和物聯網（IoT）系統，都有很大的改進空間，包括準確性、速度、計算能力和整體功耗。

本書介紹了支持高速處理器的高效機器學習和深度學習模型，這些處理器具有可重配置的架構，如圖形處理單元（GPU）和現場可編程閘陣列（FPGA），或任何混合系統。無論是在領域或實驗室工作的資深工程師或科學家，還是學生或學者，這本書都是任何圖書館必備的資源。

Suman Lata Tripathi, PhD, is a professor at Lovely Professional University with more than 21 years of experience in academics. She has published more than 103 research papers in refereed journals and conferences. She has organized several workshops, summer internships, and expert lectures for students, and she has worked as a session chair, conference steering committee member, editorial board member, and reviewer for IEEE journals and conferences. She has published three books and currently has multiple volumes scheduled for publication from Wiley-Scrivener.

Mufti Mahmud, PhD, is an associate professor of cognitive computing at the Department of Computer Science of Nottingham Trent University, UK. He is the Coordinator of the Computer Science and Informatics Unit of Assessment of Research Excellence Framework at NTU and the deputy group leader of the Interactive Systems Research Group and the Cognitive Computing & Brain Informatics research group. He is also an active member of the Computing and Informatics Research Centre and the Medical Technologies Innovation Facility. He is a member of numerous societies and research committees.

Suman Lata Tripathi, PhD，是印度Lovely Professional University的教授，擁有超過21年的學術經驗。她在被引用的期刊和會議上發表了超過103篇研究論文。她組織了多個研討會、暑期實習和專家講座，並擔任IEEE期刊和會議的會議主席、會議指導委員會成員、編輯委員會成員和審稿人。她已出版了三本書，目前有多卷書籍計劃在Wiley-Scrivener出版。

Mufti Mahmud, PhD，是英國諾丁漢特倫特大學計算機科學系的認知計算副教授。他是NTU計算機科學和信息學單位評估研究卓越框架的協調員，也是互動系統研究小組和認知計算與腦信息學研究小組的副組長。他還是計算機和信息學研究中心和醫學技術創新設施的活躍成員。他是多個學會和研究委員會的成員。