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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

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Cover of 'Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing'

Table of Contents

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    Book Overview
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    Chapter 1 Massively Parallel Neural Processing Array (MPNA): A CNN Accelerator for Embedded Systems
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    Chapter 2 Photonic NoCs for Energy-Efficient Data-Centric Computing
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    Chapter 3 Low- and Mixed-Precision Inference Accelerators
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    Chapter 4 Designing Resource-Efficient Hardware Arithmetic for FPGA-Based Accelerators Leveraging Approximations and Mixed Quantizations
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    Chapter 5 Efficient Hardware Acceleration of Emerging Neural Networks for Embedded Machine Learning: An Industry Perspective
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    Chapter 6 An Off-Chip Memory Access Optimization for Embedded Deep Learning Systems
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    Chapter 7 In-Memory Computing for AI Accelerators: Challenges and Solutions
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    Chapter 8 Efficient Deep Learning Using Non-volatile Memory Technology in GPU Architectures
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    Chapter 9 SoC-GANs: Energy-Efficient Memory Management for System-on-Chip Generative Adversarial Networks
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    Chapter 10 Using Approximate DRAM for Enabling Energy-Efficient, High-Performance Deep Neural Network Inference
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    Chapter 11 On-Chip DNN Training for Direct Feedback Alignment in FeFET
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    Chapter 12 Platform-Based Design of Embedded Neuromorphic Systems
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    Chapter 13 Light Speed Machine Learning Inference on the Edge
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    Chapter 14 Low-Latency, Energy-Efficient In-DRAM CNN Acceleration with Bit-Parallel Unary Computing
Attention for Chapter 5: Efficient Hardware Acceleration of Emerging Neural Networks for Embedded Machine Learning: An Industry Perspective
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Chapter title
Efficient Hardware Acceleration of Emerging Neural Networks for Embedded Machine Learning: An Industry Perspective
Chapter number 5
Book title
Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Published by
Springer, Cham, January 2024
DOI 10.1007/978-3-031-19568-6_5
Book ISBNs
978-3-03-119567-9, 978-3-03-119568-6
Authors

Raha, Arnab, Sung, Raymond, Ghosh, Soumendu, Gupta, Praveen Kumar, Mathaikutty, Deepak A., Cheema, Umer I., Hyland, Kevin, Brick, Cormac, Raghunathan, Vijay

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