CvS: Classification via Segmentation For Small Datasets

Understand

Deep learning models have shown promising results in a wide range of computer vision applications across various domains.

• The success of deep learning methods relies heavily on the availability of a large amount of data.
• Deep neural networks are prone to overfitting when data is scarce.
• This problem becomes even more severe for neural network with classification head with access to only a few data points.