For computer vision and image content understanding, the low-light image becomes an
obvious challenge as it suffers from poor contrast and illumination. Hence, low-light image …

This work delves into unveiling the singularity issue latent in global attention-based
Transformers. Empirical and theoretical analyses elucidate that interrelationships among …

Deep learning models have a high application value in runoff forecasting, but their
prediction mechanism is difficult to interpret and their computational cost is high when …

Real-world image denoising is an extremely important image processing problem, which
aims to recover clean images from noisy images captured in natural environments. In recent …

Due to the complexity of the underwater environment, underwater images suffer from low-
illumination, color deviation, and blurred details. Conventional underwater image …

Recent demosaicing approaches are not effective and efficient enough as they do not make
full use of these two factors:(1) Capturing long-range spatial dependencies effiently.(2) …

Bearings are indispensable components in mechanical equipment, it is crucial to realize
accurate and reliable fault diagnosis of bearings. Traditional bearing fault diagnosis …

By seamlessly integrating wavelet transforms into the image patching stage of ViT, we
leverage the power of multi-level wavelet transforms to decompose images into a diverse …

Diabetic retinopathy (DR) is a complication of diabetes that affects the eyes by damaging the
blood vessels in the retina. High blood sugar levels can cause leakage or blockage of these …

Transformer design is the de facto standard for natural language processing tasks. The
success of the transformer design in natural language processing has lately piqued the …