Low-Power Computer Vision
portes grátis
Low-Power Computer Vision
Improve the Efficiency of Artificial Intelligence
Chen, Yiran; Lu, Yung-Hsiang; Chen, Bo; Thiruvathukal, George K.; Kim, Jaeyoun
Taylor & Francis Ltd
10/2024
438
Mole
9780367755287
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
Section I Introduction
Book Introduction
Yung-Hsiang Lu, George K. Thiruvathukal, Jaeyoun Kim, Yiran Chen, and Bo Chen
History of Low-Power Computer Vision Challenge
Yung-Hsiang Lu and Xiao Hu, Yiran Chen, Joe Spisak, Gaurav Aggarwal, Mike Zheng Shou, and George K. Thiruvathukal
Survey on Energy-Efficient Deep Neural Networks for Computer Vision
Abhinav Goel, Caleb Tung, Xiao Hu, Haobo Wang, and Yung-Hsiang Lu and George K. Thiruvathukal
Section II Competition Winners
Hardware design and software practices for efficient neural network inference Yu Wang, Xuefei Ning, Shulin Zeng, Yi Kai, Kaiyuan Guo, and Hanbo Sun, Changcheng Tang, Tianyi Lu, Shuang Liang, and Tianchen Zhao
Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search
Xin Xia, Xuefeng Xiao, and Xing Wang
Fast Adjustable Threshold For Uniform Neural Network Quantization
Alexander Goncharenko, Andrey Denisov, and Sergey Alyamkin
Power-efficient Neural Network Scheduling on Heterogeneous SoCsYing Wang, Xuyi Cai, and Xiandong Zhao
Efficient Neural Network ArchitecturesHan Cai and Song Han
Design Methodology for Low Power Image Recognition SystemsSoonhoi Ha, EunJin Jeong, Duseok Kang, Jangryul Kim, and Donghyun Kang
Guided Design for Efficient On-device Object Detection ModelTao Sheng and Yang Liu
Section III Invited Articles
Quantizing Neural Networks Marios Fournarakis, Markus Nagel, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, and Tijmen Blankevoort
A practical guide to designing efficient mobile architecturesMark Sandler and Andrew Howard
A Survey of Quantization Methods for Efficient Neural Network InferenceAmir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael Mahoney, and Kurt Keutzer
Bibliography
Index
Book Introduction
Yung-Hsiang Lu, George K. Thiruvathukal, Jaeyoun Kim, Yiran Chen, and Bo Chen
History of Low-Power Computer Vision Challenge
Yung-Hsiang Lu and Xiao Hu, Yiran Chen, Joe Spisak, Gaurav Aggarwal, Mike Zheng Shou, and George K. Thiruvathukal
Survey on Energy-Efficient Deep Neural Networks for Computer Vision
Abhinav Goel, Caleb Tung, Xiao Hu, Haobo Wang, and Yung-Hsiang Lu and George K. Thiruvathukal
Section II Competition Winners
Hardware design and software practices for efficient neural network inference Yu Wang, Xuefei Ning, Shulin Zeng, Yi Kai, Kaiyuan Guo, and Hanbo Sun, Changcheng Tang, Tianyi Lu, Shuang Liang, and Tianchen Zhao
Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search
Xin Xia, Xuefeng Xiao, and Xing Wang
Fast Adjustable Threshold For Uniform Neural Network Quantization
Alexander Goncharenko, Andrey Denisov, and Sergey Alyamkin
Power-efficient Neural Network Scheduling on Heterogeneous SoCsYing Wang, Xuyi Cai, and Xiandong Zhao
Efficient Neural Network ArchitecturesHan Cai and Song Han
Design Methodology for Low Power Image Recognition SystemsSoonhoi Ha, EunJin Jeong, Duseok Kang, Jangryul Kim, and Donghyun Kang
Guided Design for Efficient On-device Object Detection ModelTao Sheng and Yang Liu
Section III Invited Articles
Quantizing Neural Networks Marios Fournarakis, Markus Nagel, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, and Tijmen Blankevoort
A practical guide to designing efficient mobile architecturesMark Sandler and Andrew Howard
A Survey of Quantization Methods for Efficient Neural Network InferenceAmir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael Mahoney, and Kurt Keutzer
Bibliography
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
- Visão por computador
- Reconhecimento de padrões
- Teoria matemática da computação
- Aprendizagem mecânica
- As redes neurais e sistemas nebulosos
- Mobile & handheld dispositivo de programação programação / Apps
- Gráficas e aplicativos de mídia digital,
- Ciência da Computação
- Engenharia electrónica
- Tecnologia e engenharia da energia
Computer Vision;Neural Networks;Artificial Intelligence;Low Power;Image Recognition Systems;Hardware;Software;Neural Network Quantization;Deep NN Model;Convolution Layers;CNN Model;NN;Neural Network;Tsinghua University;Dart;Multiply Accumulate Operations;Quantize Weights;Convolutional Layer;Execution Time;DNN;Input Feature Maps;NN Architecture;Architecture Search;Object Detection;Search Space;Initial Learning Rate;Top-1 Accuracy;CV;Accuracy Drop;Hardware Accelerators;Seoul National University
Section I Introduction
Book Introduction
Yung-Hsiang Lu, George K. Thiruvathukal, Jaeyoun Kim, Yiran Chen, and Bo Chen
History of Low-Power Computer Vision Challenge
Yung-Hsiang Lu and Xiao Hu, Yiran Chen, Joe Spisak, Gaurav Aggarwal, Mike Zheng Shou, and George K. Thiruvathukal
Survey on Energy-Efficient Deep Neural Networks for Computer Vision
Abhinav Goel, Caleb Tung, Xiao Hu, Haobo Wang, and Yung-Hsiang Lu and George K. Thiruvathukal
Section II Competition Winners
Hardware design and software practices for efficient neural network inference Yu Wang, Xuefei Ning, Shulin Zeng, Yi Kai, Kaiyuan Guo, and Hanbo Sun, Changcheng Tang, Tianyi Lu, Shuang Liang, and Tianchen Zhao
Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search
Xin Xia, Xuefeng Xiao, and Xing Wang
Fast Adjustable Threshold For Uniform Neural Network Quantization
Alexander Goncharenko, Andrey Denisov, and Sergey Alyamkin
Power-efficient Neural Network Scheduling on Heterogeneous SoCsYing Wang, Xuyi Cai, and Xiandong Zhao
Efficient Neural Network ArchitecturesHan Cai and Song Han
Design Methodology for Low Power Image Recognition SystemsSoonhoi Ha, EunJin Jeong, Duseok Kang, Jangryul Kim, and Donghyun Kang
Guided Design for Efficient On-device Object Detection ModelTao Sheng and Yang Liu
Section III Invited Articles
Quantizing Neural Networks Marios Fournarakis, Markus Nagel, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, and Tijmen Blankevoort
A practical guide to designing efficient mobile architecturesMark Sandler and Andrew Howard
A Survey of Quantization Methods for Efficient Neural Network InferenceAmir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael Mahoney, and Kurt Keutzer
Bibliography
Index
Book Introduction
Yung-Hsiang Lu, George K. Thiruvathukal, Jaeyoun Kim, Yiran Chen, and Bo Chen
History of Low-Power Computer Vision Challenge
Yung-Hsiang Lu and Xiao Hu, Yiran Chen, Joe Spisak, Gaurav Aggarwal, Mike Zheng Shou, and George K. Thiruvathukal
Survey on Energy-Efficient Deep Neural Networks for Computer Vision
Abhinav Goel, Caleb Tung, Xiao Hu, Haobo Wang, and Yung-Hsiang Lu and George K. Thiruvathukal
Section II Competition Winners
Hardware design and software practices for efficient neural network inference Yu Wang, Xuefei Ning, Shulin Zeng, Yi Kai, Kaiyuan Guo, and Hanbo Sun, Changcheng Tang, Tianyi Lu, Shuang Liang, and Tianchen Zhao
Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search
Xin Xia, Xuefeng Xiao, and Xing Wang
Fast Adjustable Threshold For Uniform Neural Network Quantization
Alexander Goncharenko, Andrey Denisov, and Sergey Alyamkin
Power-efficient Neural Network Scheduling on Heterogeneous SoCsYing Wang, Xuyi Cai, and Xiandong Zhao
Efficient Neural Network ArchitecturesHan Cai and Song Han
Design Methodology for Low Power Image Recognition SystemsSoonhoi Ha, EunJin Jeong, Duseok Kang, Jangryul Kim, and Donghyun Kang
Guided Design for Efficient On-device Object Detection ModelTao Sheng and Yang Liu
Section III Invited Articles
Quantizing Neural Networks Marios Fournarakis, Markus Nagel, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, and Tijmen Blankevoort
A practical guide to designing efficient mobile architecturesMark Sandler and Andrew Howard
A Survey of Quantization Methods for Efficient Neural Network InferenceAmir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael Mahoney, and Kurt Keutzer
Bibliography
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
- Visão por computador
- Reconhecimento de padrões
- Teoria matemática da computação
- Aprendizagem mecânica
- As redes neurais e sistemas nebulosos
- Mobile & handheld dispositivo de programação programação / Apps
- Gráficas e aplicativos de mídia digital,
- Ciência da Computação
- Engenharia electrónica
- Tecnologia e engenharia da energia
Computer Vision;Neural Networks;Artificial Intelligence;Low Power;Image Recognition Systems;Hardware;Software;Neural Network Quantization;Deep NN Model;Convolution Layers;CNN Model;NN;Neural Network;Tsinghua University;Dart;Multiply Accumulate Operations;Quantize Weights;Convolutional Layer;Execution Time;DNN;Input Feature Maps;NN Architecture;Architecture Search;Object Detection;Search Space;Initial Learning Rate;Top-1 Accuracy;CV;Accuracy Drop;Hardware Accelerators;Seoul National University
