Rajeev Tripathi You might wanna check out this overview, including datasets, models, methods and code: https://paperswithcode.com/task/anomaly-detection

Thank you sir

The choice of approach totally depends on the specific dataset, available resources, research objectives, and most importantly the desired level of accuracy. You can experiment with different methods to find the one that best suits your needs.

There are several approaches you can explore to detect anomalies in image datasets. You can explore different machine and deep learning algorithms, such as Autoencoders, Isolation Forests, Support Vector Machine, Convolutional Neural Networks, and Contrastive Learning. Additionally, you can explore hybrid approaches that combine machine learning, computer vision, and deep learning techniques to extract relevant features from images to detect anomalies.