Aims/Objectives
Centre for Visual Computing and Sustainable Intelligence (CVCSI) focuses on basic and advanced research in computer vision, image processing and machine learning with a strong focus on sustainability in agriculture and health. Our mission is to develop innovative solutions that enhance the efficiency, productivity, and sustainability of agricultural practices and improve health outcomes through cutting-edge research in visual computing and AI. The activity of this Centre overlaps the traditional areas of Computer Vision, Image Processing, Pattern Recognition and Machine Learning. The Centre aims to keep the right balance between cutting-edge academic research and impactful applied research. The centre spans various domains of research, including but not limited to:
- Machine learning and Deep Learning.
- Computer Vision.
- Image Processing
- Application of Machine learning and deep learning for Astronomical study
- Natural Language Processing
CVCSI centre is equipped with state-of-the-art facilities and computational resources, providing an ideal environment for impactful research and collaboration. We foster strong partnerships with industry leaders, academic institutions, and government agencies to drive innovation and translate our research into practical applications.
In addition to research, the Centre will also offer educational programs, such as seminars, workshops, and internships.
Centre’s Vision:
To provide a platform for conducting pioneering research and innovation in computer vision and pattern recognition, driving sustainable solutions in agriculture and health.
Members
Internal:
Dr. Shabbeer BashaAssociate Professor, SoCSE (Director)
Dr. Anand NarasimhamurthyProfessor, SoCSE
Mr. Jaison JoshyAssistant Professor, SoCSE
Mr. Shoeb Ahmad Assistant Professor, SoCSE
Ms. Shobha HR Teaching Assistant, SoCSE
Mr. Paras Negi Teaching Assistant, SoCSE
External:
Dr. Snehasis Mukherjee Shiv Nadar University, Noida
Dr. Shiv Ram DubeyIIIT Allahabad
Dr. Jayachandra DakalaLytx India, Bangalore
Publications
- Sarvani CH, Mrinmoy Ghorai, Shabbeer Basha, “A Simple Hybrid Filter Pruning for Efficient Edge Inference”, Neural Computing and Applications (Impact Factor: 4.5), Springer,
- H.Shabbeer Basha, Debapriya Tula, Sravan Kumar Vinakota, Shiv Ram Dubey, Target Aware Architecture Search and Compression for Efficient Knowledge Transfer, Multimedia Systems (Impact factor: 3.9), Springer, 2024.
- H.Shabbeer Basha, Mohammad Farazuddin, Viswanath Pulabaigari, Shiv Ram Dubey, Snehasis Mukherjee, “Deep Model Compression based on the Training History”, Neurocomputing (Impact factor: 6), Elsevier, 2024.
Guest Lecture Delivered by the members
- Dr. Shabbeer Basha delivered a session on “Regularization in Neural Networks, improving training of NNs”, organized by VNRVJIT, Hyderabad, 7th February 2024.
- Dr. Shabbeer Basha delivered an invited sessions on “Machine learning and Deep learning algorithms with Research perspective” organized (online) by Vardhaman College of Engineering, Hyderabad, 18th to 22nd December 2023.
- Dr. Shabbeer Basha delivered a session as a resource person for the ” Few-shot and Active Learning methods” at WADLA-3.0 organized by Indian Institute of Information Technology Sri City on 15th December 2023.
- Dr. Shabbeer Basha delivered a session on “Maximizing CNN Performance on a Tight Budget: Active Learning Strategies for Efficient Annotation”, organized by IIIT Sri City, 28th September 2023.
