Ongoing Research Projects
Explore the groundbreaking projects in the field of computer vision and AI, developed to solve real-world challenges across various industries
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Explainable AI Tools for Detection and Classification of SONAR Imagery for Real-world Defence Applications (2023-2025)
Explainable AI Tools for Detection and Classification of SONAR Imagery for Real-world Defence Applications (2023-2025)
Funding agency: Defence Research and Development Organisation (DRDO)
Grant amount: ₹ 33,92,000
PI: Dr. Athira Nambiar
Co-PI: Dr. Suresh Rajendran, IIT Madras
This project focuses on developing explainable AI models for the detection and classification of underwater sonar images. By utilizing self-explainable deep learning models, the system predicts targets in sonar imagery and provides clear explanations for the predictions. This transparency enables users to interpret the results and understand the reasoning behind them.
DRDO
DRDO
Development of Active Learning Algorithms for Human-in-loop AI Systems for Satellite Imagery Analysis (2024-2026)
Development of Active Learning Algorithms for Human-in-loop AI Systems for Satellite Imagery Analysis (2024-2026)
Funding agency: Indian Space Research Organization (ISRO)
Grant amount: ₹ 25,66,160
PI: Dr. Athira Nambiar
Co-PI: Dr. Maragatham, SRMIST
This project integrates human intervention with explainable AI tools to enable domain experts to actively contribute to the learning process. The system leverages the "Human-in-the-loop" paradigm, enabling experts to augment AI's knowledge and improve satellite imagery analysis. Through Explainable AI (XAI), human experts receive intuitive reasoning behind the machine's decisions and provide valuable feedback to enhance image segmentation tasks.
ISRO
ISRO
Meta-learning Framework for Predictive Analysis in Magnetic Resonance Imaging of Ischemic Stroke Lesions (2024-2027)
Meta-learning Framework for Predictive Analysis in Magnetic Resonance Imaging of Ischemic Stroke Lesions (2024-2027)
Funding agency: Department of Science and Technology, Science and Engineering Research Board-Core Research Grant (DST SERB-CRG)
Grant amount: ₹ 30,71,220
PI: Dr. Athira Nambiar
Co-PI: Dr. A. Senthil Kumar, Dept. of Radiology, SRMIST.
This research develops a computationally efficient meta-learning model to address data limitations and domain adaptation challenges in medical imaging. The framework is applied to predictive tasks in MRI of ischemic stroke lesions, enhancing the adaptability and robustness of AI models in medical domains. The project focuses on improving multi-task learning to make AI models more accurate and capable of handling limited data challenges.
DST
DST
Pilot Study on Deep Learning-based Non-invasive Ultrasound Tool for Assessing Sexual Maturation of Asian Sea Bass Lates calcarifer (2023-2025)
Pilot Study on Deep Learning-based Non-invasive Ultrasound Tool for Assessing Sexual Maturation of Asian Sea Bass Lates calcarifer (2023-2025)
Funding agency: Ministry of Earth Sciences
Grant amount: ₹ 30,00,000
PI: Dr. R. Annie Uthra
Co-PI: Dr. Saad Yunus sait, SRMIST
This project aims to develop a non-invasive ultrasound technique to assess the sex and gonadal maturity of Asian Sea Bass, critical for brackishwater aquaculture. By using deep learning for image processing, this method provides a stress-free way to monitor gonadal stages, improving the reproductive success of brooders. The system uses techniques such as segmentation, feature extraction, transfer learning, and GANs to classify gonadal stages with high accuracy, and its results are validated with histology data.
MoES
MoES
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