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Found 5 papers, 1 papers with code
A Resource-Efficient Training Framework for Remote Sensing Text--Image Retrieval
To reduce the training memory consumption, we propose the Focus-Adapter module, which adopts a side branch structure.
Empirical Analysis of AI-based Energy Management in Electric Vehicles: A Case Study on Reinforcement Learning
The empirical analysis is developed in four aspects: algorithm, perception and decision granularity, hyperparameters, and reward function.
Potential Auto-driving Threat: Universal Rain-removal Attack
The problem of robustness in adverse weather conditions is considered a significant challenge for computer vision algorithms in the applicants of autonomous driving.
Double Similarity Distillation for Semantic Image Segmentation
In this paper, motivated by the residual learning and global aggregation, we propose a simple yet general and effective knowledge distillation framework called double similarity distillation (DSD) to improve the classification accuracy of all existing compact networks by capturing the similarity knowledge in pixel and category dimensions, respectively.
FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery
In this paper, we propose a novel benchmark dataset with more than 1 million instances and more than 15, 000 images for Fine-grAined object recognItion in high-Resolution remote sensing imagery which is named as FAIR1M.
