Deep architectures are playing the most important role in the area of machine learning and are considered as the future technology and anticipated a complete paradigm shift in the area of artificial intelligence by the researchers. It is considered to be one of the most active areas of research in signal, image, vision and biometrics and comprises of supervised and unsupervised models of approach for detection/ recognition/ classification/ synthesization of objects.

The proposed one-week course will be comprising of approximately 20 Hrs of sessions, including the hands on demonstration. This short-term course will be useful for the PG and PhD Students and the Young Professionals working in the recent state of the art methods in AI/ ML/DL for a variety of applications of Signal. Image Processing, Computer Vision and Biometrics and pertains to how all of the approaches can be applied to research problems in real life. The course also covers essentials of machine learning, deep neural networks as well as the other models how they can be applied to solve practical problems in signal processing, image processing and computer vision. The recent trends, such as Adversarial Learning and Transformer networks will be also covered.

1. Building awareness towards deep learning architectures.
2. Building the technical capacity in the area of Signal, Image, and Vision Processing via deep architectures.
3. Building communities of research students, educator, RD, and Industry persons in this emerging area of research and development.
4. Providing hands-on tutorial sessions, where the participants can experiment with concepts and methods

1. Advances in Deep Architectures
2. Applications to Signal, Image and Video Processing
3. Fairness, Accountability, Transparency, and Ethics in Deep Learning
4. Adversarial Learning
5. Transformers - A new wave in Deep Learning
6. Other Issues and Applications of Deep Learning