Development and validation of deep learning algorithm using ultra-wide-field Optos images for early detection of Diabetic Retinopathy in 45-degree single-field, as Co-PI,
Funded by UNSW School of Optometry and Vision Science: Diabetes Research Grant from the Elizabeth O'Beirne and Robert and Emmy Mather Trust Fund, Ongoing.
Mobile App for assisting Indian
farmers in improving yield by automatic identification of plant diseases (Rice
and Tomato) [ Funded by DST SYST, Ongoing] as PI.
India suffers from annual crop loss of many crores of rupees
owing to pest and disease infestation, according to a study by Assocham and Yes
bank. Different plants are infested by different diseases; while some are
caused by fungi, some are caused by bacteria and some by viruses. This project aims in automatically
identifying key diseases in specific plants using mobile application, so that
the farmers can be benefitted. The image database pertaining to the Indian
subcontinent, would be employed to train a model that can automatically predict
plant diseases. Both traditional image processing techniques as well as the
recent advances in convolutional neural networks would be employed for this
purpose.
India Innovation Growth Program 2.0 [Funded by DST - Lockheed Martin - TATA Trusts, completed]
Faculty Advisor: Dr. Sundaresan Raman
Team: Faraaz Ahmad, Sashakt Tripathi, Harshit Awasthi
Food Sense: A Framework for Safe Storage, Preparation and Delivery of Food [Funded by BITS Pilani, Completed] as PI.