Machine Learning on Commodity Tiny Devices
portes grátis
Machine Learning on Commodity Tiny Devices
Theory and Practice
Zhou, Qihua; Guo, Song
Taylor & Francis Ltd
12/2022
250
Dura
Inglês
9781032374239
15 a 20 dias
Descrição não disponível.
1. Introduction 2. Fundamentals: On-device Learning Paradigm 3. Preliminary: Theories and Algorithms 4. Model-level Design: Computation Acceleration and Communication Saving 5. Hardware-level Design: Neural Engines and Tensor Accelerators 6. Infrastructure-level Design: Serverless and Decentralized Machine Learning 7. System-level Design: from Standalone to Clusters 8. Application: Image-based Visual Perception 9. Application: Video-based Real-time Processing 10. Application: Privacy, Security, Robustness and Trustworthiness in Edge AI
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Edge AI;edge intelligence;neural network design;Computation;SE Module;CNN Model;Stochastic Gradient Descent;SVM Classifier;Image Classification Tasks;Convolutional Layer;FL;Serverless Computing;LR Input;Human Motion Tracking;Max Pooling Layer;Optical Flow;GPU Cluster;LR Image;GPU Acceleration;Video Recognition;Non-Linear Neural Networks;Hr Image;Original RGB Image;RGB Camera;Local Updates;Testset;Semantic Segmentation;Edge Devices;Low Rank Factorization
1. Introduction 2. Fundamentals: On-device Learning Paradigm 3. Preliminary: Theories and Algorithms 4. Model-level Design: Computation Acceleration and Communication Saving 5. Hardware-level Design: Neural Engines and Tensor Accelerators 6. Infrastructure-level Design: Serverless and Decentralized Machine Learning 7. System-level Design: from Standalone to Clusters 8. Application: Image-based Visual Perception 9. Application: Video-based Real-time Processing 10. Application: Privacy, Security, Robustness and Trustworthiness in Edge AI
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Edge AI;edge intelligence;neural network design;Computation;SE Module;CNN Model;Stochastic Gradient Descent;SVM Classifier;Image Classification Tasks;Convolutional Layer;FL;Serverless Computing;LR Input;Human Motion Tracking;Max Pooling Layer;Optical Flow;GPU Cluster;LR Image;GPU Acceleration;Video Recognition;Non-Linear Neural Networks;Hr Image;Original RGB Image;RGB Camera;Local Updates;Testset;Semantic Segmentation;Edge Devices;Low Rank Factorization
