Image Classifier

Image classifiers are computer vision systems designed to categorize images into predefined classes, with recent research focusing on improving their accuracy, robustness, and explainability. Current efforts involve developing more efficient architectures (like Vision Transformers and EfficientNets), mitigating biases through techniques such as counterfactual analysis and subgroup discovery, and enhancing interpretability using multimodal explanations that integrate visual and textual information. These advancements are crucial for building reliable and trustworthy image classifiers, impacting diverse fields from medical diagnosis to autonomous driving by improving both performance and user understanding of model decisions.