Image Classification Datasets

Image classification datasets are crucial for training and evaluating computer vision models, with research focusing on improving data quality, addressing biases, and enhancing model generalization. Current efforts involve developing novel training frameworks like bilevel optimization and exploring architectures such as Vision Transformers and state-space models to improve accuracy and efficiency across diverse datasets, including those with complex scenes or subjective concepts. This research is vital for advancing the field of computer vision and enabling the development of more robust, fair, and reliable image classification systems for various applications.