TY - BOOK ID - 103609505 TI - Deep learning on edge computing devices : design challenges of algorithm and architecture PY - 2022 SN - 0323857833 0323909272 9780323909273 9780323857833 PB - Amsterdam, Netherlands : Elsevier, DB - UniCat KW - Deep learning (Machine learning) KW - Edge computing. KW - Electronic data processing KW - Learning, Deep (Machine learning) KW - Iterative methods (Mathematics) KW - Machine learning KW - Distributed processing KW - Computer input-output equipment. UR - https://www.unicat.be/uniCat?func=search&query=sysid:103609505 AB - Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and other applications by presenting neural network algorithms and hardware design optimization approaches for Edge-deep learning. Applications are introduced in each section, and a comprehensive example, smart surveillance cameras, is presented at the end of the book, integrating innovation in both algorithm and hardware architecture. Structured into three parts, the book covers core concepts, theories and algorithms and architecture optimization. ER -