Introduction Oral squamous cell carcinoma (OSCC) presents a significant global health
challenge. The integration of artificial intelligence (AI) and computer vision holds promise for …

The" pre-training and fine-tuning" paradigm in addressing long-tailed recognition tasks has
sparked significant interest since the emergence of large vision-language models like the …

Consumer reviews on social media is providing valuable opportunities for electric vehicle
companies to investigate product failure information. By noticing the fact that consumers …

Cancer diseases constitute one of the most significant societal challenges. In this paper, we
introduce a novel histopathological dataset for prostate cancer detection. The proposed …

The oxygen saturation level in the blood (SaO 2) is crucial for health, particularly in relation
to sleep-related breathing disorders. However, continuous monitoring of SaO 2 is time …

Abstract Vision Transformer (ViT) has emerged as a prominent architecture for various
computer vision tasks. In ViT we divide the input image into patch tokens and process them …

Real-world data often exhibits a long-tailed distribution, where the number of training
samples for head classes far exceeds that of tail classes. This class imbalance phenomenon …

Deep neural networks have succeeded in learning balanced and imbalanced data in the
field of pneumonia diagnosis. However, both require separate model designs in their …

Model Weight Averaging (MWA) is a technique that seeks to enhance model's performance
by averaging the weights of multiple trained models. This paper first empirically finds that 1) …

Imbalanced label distribution is usually the case for real-world data, which poses a
challenge for training unbiased recognition model. In this paper, we study two underlying …