01049nam0 22002771i 450 UON0004502820231205102202.39809-07-13232-420020107d1987 |0itac50 baengGB|||| 1||||Eastern TurkeyAn architectural and archaeological surveyT.A. SinclairLondonThames and Hudson1987 - v.ill. ; 25 cposs. il vol. IARCHITETTURATURCHIA ORIENTALEUONC015535FIGBOxfordUONL000029VO XIVICINO ORIENTE - ARCHITETTURAASINCLAIRT. A.UONV028635649213The Pindar PressUONV253069650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00045028SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI VO XI 004 SI SA 57612 7 004 Eastern Turkey1158694UNIOR03036nam 22004813 450 991101951070332120250430221013.097813941718979781394171910(MiAaPQ)EBC30786531(CKB)28495736400041(Au-PeEL)EBL30786531(Exl-AI)30786531(OCoLC)1403973244(EXLCZ)992849573640004120231016d2023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAccelerators for Convolutional Neural Networks1st ed.Newark :John Wiley & Sons, Incorporated,2023.©2024.1 online resource (307 pages)9781394171880 Cover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- Part I Overview -- Chapter 1 Introduction -- 1.1 History and Applications -- 1.2 Pitfalls of High‐Accuracy DNNs/CNNs -- 1.2.1 Compute and Energy Bottleneck -- 1.2.2 Sparsity Considerations -- 1.3 Chapter Summary -- Chapter 2 Overview of Convolutional Neural Networks -- 2.1 Deep Neural Network Architecture -- 2.2 Convolutional Neural Network Architecture -- 2.2.1 Data Preparation -- 2.2.2 Building Blocks of CNNs -- 2.2.2.1 Convolutional Layers -- 2.2.2.2 Pooling Layers -- 2.2.2.3 Fully Connected Layers -- 2.2.3 Parameters of CNNs -- 2.2.4 Hyperparameters of CNNs -- 2.2.4.1 Hyperparameters Related to Network Structure -- 2.2.4.2 Hyperparameters Related to Training -- 2.2.4.3 Hyperparameter Tuning -- 2.3 Popular CNN Models -- 2.3.1 AlexNet -- 2.3.2 VGGNet -- 2.3.3 GoogleNetGenerated by AI.This book provides an in-depth exploration of accelerators for convolutional neural networks (CNNs), a pivotal component in the field of artificial intelligence and computer vision. It covers the architecture of CNNs, compressive coding techniques, and the design of both dense and sparse CNN accelerators. The text discusses hardware and software co-design and scheduling strategies to optimize CNN performance. Aimed at students, researchers, and professionals in computer architecture and hardware design, the book serves as a comprehensive reference on the development and implementation of CNN accelerators.Generated by AI.Neural networks (Computer science)Generated by AIComputer architectureGenerated by AINeural networks (Computer science)Computer architecture006.32Munir Arslan848010Kong Joonho1839620Qureshi Mahmood Azhar1839621MiAaPQMiAaPQMiAaPQ9911019510703321Accelerators for Convolutional Neural Networks4418898UNINA