Supervised Compression for Resource-Constrained Edge Computing Systems

There has been much interest in deploying deep learning algorithms on low-powered devices, including smart-phones, drones, and medical sensors. However, full-scale deep neural networks are often too resource-intensive in terms of energy and storage. As a result, the bulk part of the machine learning...

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Bibliographic Details
Main Authors: Matsubara, Yoshitomo, Yang, Ruihan, Levorato, Marco, Mandt, Stephan
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
Deep learning
Entropy coding
Image coding
Rate-distortion
Stochastic processes
Training
Vision Systems and Applications Image Processing
Image Processing -> Image Compression
Online Access:Request full text
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