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Found 4 papers, 2 papers with code
Enhanced Urban Region Profiling with Adversarial Self-Supervised Learning
Urban region profiling is pivotal for smart cities, but mining fine-grained semantics from noisy and incomplete urban data remains challenging.
Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning
Meanwhile, we design a supervised task to learn more robust representations and facilitate the contrastive learning process.
MEAOD: Model Extraction Attack against Object Detectors
The widespread use of deep learning technology across various industries has made deep neural network models highly valuable and, as a result, attractive targets for potential attackers.
Sharp Eyes: A Salient Object Detector Working The Same Way as Human Visual Characteristics
In the OS branch, we first aggregate multi-level features to adaptively select complementary components, and then feed the saliency features with expanded boundary into aggregated features to guide the network obtain complete prediction.
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