Five-Day Faculty Development Programme on AI in Image Processing and Pattern Recognition

10th - 14th August 2026

Dronacharya College of Engineering, Gurugram, in collaboration with National Institute of Technology (NIT), Patna, under the Electronics & ICT Academy, NIT Patna, successfully organized a Five-Day Faculty Development Programme (FDP) on “Recent Developments of Artificial Intelligence in Image Processing and Pattern Recognition” from 10th to 14th August 2026 in hybrid mode. Supported by the Ministry of Electronics and Information Technology (MeitY), Government of India, the programme brought together faculty members, researchers, scholars and professionals for an intensive learning experience focused on emerging developments in Artificial Intelligence, computer vision, image processing, pattern recognition and medical imaging.

Guided by Dr. Satish Yadav, Hon’ble Chairman, DCE, as Chief Patron and Prof. (Dr.) B.M.K. Prasad, Director, DCE, as Patron, the programme was convened by Prof. (Dr.) Isha Malhotra, Principal; Prof. Yashvardhan Soni, HoD, CSE-AIML; and Dr. Kavery Verma, Assistant Professor, ECE. Dr. Manoj Kumar, Mr. Naveen, Dr. Bambam Kumar and Dr. Ashish Kumar Bhandari served as Co-Coordinators. Their collective efforts facilitated a structured five-day learning programme comprising approximately 40 hours of expert-led lectures, interactive discussions, demonstrations and hands-on sessions.

Beginning with the fundamentals of digital image processing and computer vision, Day 1 introduced participants to image representation, enhancement, histogram processing, filtering, edge detection and image segmentation. Prof. Sheli Sinha Chaudhuri, Jadavpur University, and Dr. Rajib Kumar Jha, IIT Patna, shared expert perspectives on image-processing fundamentals and segmentation techniques. Practical sessions led by Ms. Trisha Paul, Jadavpur University, and Ms. Hrijuta Datta, NIT Agartala, provided hands-on exposure to Python, NumPy, OpenCV and Google Colab, including applications in medical imaging and diabetic retinopathy analysis.

Advanced AI applications took centre stage on Day 2, with discussions around deep learning-based Computer-Aided Diagnosis, GAN-based data augmentation and transfer learning. Dr. Nilanjan Dey, Techno International New Town, highlighted challenges and emerging solutions in AI-driven diagnostic systems, while Dr. Mausam Chouksey, MITS Gwalior, explored pretrained models, fine-tuning, zero-shot and few-shot learning. Hands-on activities further introduced participants to image segmentation, ResNet18, medical datasets, diabetic retinopathy classification and Grad-CAM-based explainable AI, connecting theoretical concepts with practical implementation.

A strong focus on AI-enabled healthcare and advanced medical image processing marked Day 3. Prof. Santi P. Maity, IIEST Shibpur, discussed AI applications in medical imaging, Edge-IoT, Digital Twins, GANs and intelligent healthcare systems. Dr. Kavery Verma, DCE, presented approaches for MRI image restoration and enhancement, particularly for Rician-noise-corrupted images. Complementary laboratory sessions covered Python-based image processing and deep-learning-based colorectal polyp segmentation, offering participants valuable exposure to contemporary medical-imaging research.

Contemporary developments in machine learning, deep learning, Transformers and computer vision formed the core of Day 4. Dr. Gopal Singh Phartiyal, BITS Pilani, explored Vision Transformers, self-attention, image classification, segmentation and YOLO-based object detection. Prof. Debotosh Bhattacharjee, Jadavpur University, focused on deep image processing, enhancement, denoising and restoration, while Dr. Kankanala Srinivas, VIT Hyderabad, discussed neural-network training and GHGL-Net for underwater image restoration. A practical session on ensemble learning for breast cancer classification further demonstrated techniques such as voting, bagging, boosting and stacking.

Bringing together several emerging research directions, Day 5 focused on AI-powered medical imaging and next-generation diagnostics. Prof. Karm Veer Arya, ABV-IIITM Gwalior, discussed Explainable AI, Vision Transformers, foundation models, federated learning, digital twins and multimodal learning. Ms. Manvi Jha, University of Illinois Urbana-Champaign, explored dark-image enhancement using MultiscaleRetinex and Low-Rank Minimization, while Dr. Ravi Kumar, Muzaffarpur Institute of Technology, addressed retinal image enhancement and restoration. A technical quiz provided an engaging culmination to the learning sessions, followed by the Vote of Thanks delivered by Dr. Kavery Verma.

Through its blend of expert lectures, practical demonstrations and hands-on learning, the FDP created a valuable platform for faculty upskilling, research collaboration and knowledge exchange. Participants gained insights into cutting-edge areas including computer vision, deep learning, medical image analysis, Transformers, explainable AI, image restoration and AI-driven healthcare. The programme strengthened the connection between emerging research and practical applications while encouraging participants to explore innovative approaches for teaching, research and the development of intelligent visual systems.