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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 26–50 of 96 papers

TitleStatusHype
Dynamic Submodular Maximization—0
End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement—0
End-to-End Learnable Multi-Scale Feature Compression for VCM—0
Enhancing Drug Discovery: Autoencoder-Based Latent Space Augmentation for Improved Molecular Solubility Prediction using LatMixSol—0
Feature Compression for Cloud-Edge Multimodal 3D Object Detection—0
Feature Compression for Rate Constrained Object Detection on the Edge—0
Fusion: Towards Automated ICD Coding via Feature Compression—0
Generative Map Priors for Collaborative BEV Semantic Segmentation—0
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks—0
Hierarchical Semantic Compression for Consistent Image Semantic Restoration—0
In Defense of Clip-based Video Relation Detection—0
Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing—0
JointRF: End-to-End Joint Optimization for Dynamic Neural Radiance Field Representation and Compression—0
Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction—0
Connecting Compression Spaces with Transformer for Approximate Nearest Neighbor Search—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
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal—0
Attention-based Feature Compression for CNN Inference Offloading in Edge Computing—0
Categorical Feature Compression via Submodular Optimization—0
Chromatic Learning for Sparse Datasets—0
Collaborative Intelligence: Challenges and Opportunities—0
Communication-Computation Efficient Device-Edge Co-Inference via AutoML—0
Compact Representation for Image Classification: To Choose or to Compress?—0
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