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Enhancing Landmark Detection in Cluttered Real-World Scenarios with Vision Transformers
Visual place recognition tasks often encounter significant challenges in landmark detection due to the presence of irrelevant objects such as humans, cars, and trees, despite the remarkable progress achieved by previous models, especially in the context of transformers.
Mitigating Bias: Enhancing Image Classification by Improving Model Explanations
In this paper, we propose a novel approach to address this issue and improve the learning of main concepts by image classifiers.
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