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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 61–70 of 96 papers

TitleStatusHype
Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks—0
Toward Scalable Image Feature Compression: A Content-Adaptive and Diffusion-Based Approach—0
Towards unlocking the mystery of adversarial fragility of neural networks—0
UCS: A Universal Model for Curvilinear Structure Segmentation—0
Vertical Federated Image Segmentation—0
Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics—0
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics—0
The Road to On-board Change Detection: A Lightweight Patch-Level Change Detection Network via Exploring the Potential of Pruning and Pooling—0
Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization—0
An Efficient Large Recommendation Model: Towards a Resource-Optimal Scaling Law—0
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