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Feature Compression

Compress data for machine interpretability to perform downstream tasks, rather than for human perception.

Papers

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Showing 76–96 of 96 papers

TitleStatusHype
Selective Feature Compression for Efficient Activity Recognition Inference—0
Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction—0
Collaborative Intelligence: Challenges and Opportunities—0
Dynamic Submodular Maximization—0
PIDNet: An Efficient Network for Dynamic Pedestrian Intrusion Detection—0
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning—0
Chromatic Learning for Sparse Datasets—0
Joint Device-Edge Inference over Wireless Links with Pruning—0
End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement—0
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics—0
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal—0
BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference SystemsCode0
Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks—0
Categorical Feature Compression via Submodular Optimization—0
Comparing of Term Clustering Frameworks for Modular Ontology Learning—0
Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing—0
Near-Lossless Deep Feature Compression for Collaborative Intelligence—0
Context-aware Deep Feature Compression for High-speed Visual TrackingCode0
Deep feature compression for collaborative object detection—0
Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks—0
Compact Representation for Image Classification: To Choose or to Compress?—0
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