Learning Accurate Performance Predictors for Ultrafast Automated Model Compression

In this paper, we propose an ultrafast automated model compression framework called SeerNet for flexible network deployment. Conventional non-differen-tiable methods discretely search the desirable compression policy based on the accuracy from exhaustively trained lightweight models, and existing di...

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Bibliographic Details
Published in:International journal of computer vision Vol. 131; no. 7; pp. 1761 - 1783
Main Authors: Wang, Ziwei, Lu, Jiwen, Xiao, Han, Liu, Shengyu, Zhou, Jie
Format: Journal Article
Language:English
Published: New York Springer US 01.07.2023
Springer
Springer Nature B.V
Subjects:
Accuracy
Artificial Intelligence
Automation
Complexity
Computational efficiency
Computer Imaging
Computer Science
Computing costs
Image classification
Image compression
Image Processing and Computer Vision
Object recognition
Optimization
Pattern Recognition
Pattern Recognition and Graphics
Performance prediction
Searching
Vision
Compression policy optimization
Performance predictor
Evolutionary search
Uncertainty estimation
Automated model compression
ISSN:0920-5691, 1573-1405
Online Access:Get full text
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