1 citations · 1 across the 3 of their papers we have counts for
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Vision KAN: Towards an Attention-Free Backbone for Vision with Kolmogorov-Arnold Networks
Zhuoqin Yang, Jiansong Zhang, Xiaoling Luo +3
Attention mechanisms have become a key module in modern vision backbones due to their ability to model long-range dependencies. However, their quadratic complexity in sequence leng…
LightQANet: Quantized and Adaptive Feature Learning for Low-Light Image Enhancement
Xu Wu, Zhihui Lai, Xianxu Hou +3
Low-light image enhancement (LLIE) aims to improve illumination while preserving high-quality color and texture. However, existing methods often fail to extract reliable feature re…
MedKAN: An Advanced Kolmogorov-Arnold Network for Medical Image Classification
Zhuoqin Yang, Jiansong Zhang, Xiaoling Luo +2
Recent advancements in deep learning for image classification predominantly rely on convolutional neural networks (CNNs) or Transformer-based architectures. However, these models f…
Low-Light Enhancement Effect on Classification and Detection: An Empirical Study
Xu Wu, Zhihui Lai, Zhou Jie +4
Low-light images are commonly encountered in real-world scenarios, and numerous low-light image enhancement (LLIE) methods have been proposed to improve the visibility of these ima…
CodeEnhance: A Codebook-Driven Approach for Low-Light Image Enhancement
Xu Wu, XianXu Hou, Zhihui Lai +4
Low-light image enhancement (LLIE) aims to improve low-illumination images. However, existing methods face two challenges: (1) uncertainty in restoration from diverse brightness de…