Image Classification Model

Image classification models aim to automatically categorize images into predefined classes, a fundamental task in computer vision with broad applications. Current research emphasizes improving model robustness against adversarial attacks and noisy data, enhancing interpretability through techniques like counterfactual explanations and prototype generation, and addressing fairness concerns arising from biases in training data. These efforts leverage various architectures, including convolutional neural networks and vision transformers, and focus on developing more reliable and trustworthy AI systems for diverse real-world applications.