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The workshop will be conducted in hybrid mode. Online link of the workshop will be shared only with the registered participants who indicate their willingness to attend the workshop online.
About Workshop
Welcome to our 5-day intensive workshop on Image Segmentation, a foundational pillar in computer vision and machine learning. This workshop is meticulously designed to bridge the gap between theoretical knowledge and practical expertise in the latest image segmentation techniques. Each day is structured into two comprehensive sessions; the morning session will help build theoretical foundations of various segmentation models and approaches, starting from the basics to more advanced topics. In the afternoon, participants will gain experience with guided practical sessions, applying what they've learned to real-world datasets using PyTorch, a leading deep learning framework.
Whether you're a budding data scientist, a seasoned researcher, or a tech enthusiast eager to delve into image segmentation, this workshop promises a blend of theoretical learning and hands-on experience. Prepare to explore everything from early deep learning models to cutting-edge techniques in semi-supervised learning. Join us in demystifying the complex world of image segmentation and equip yourself with the skills to innovate and excel in your machine learning projects.
Prof. Anubha Gupta (workshop organizer) would like to thank SERB, DST for the SERB POWER Fellowship grant no. SPF/2021/000209 for the support of this outreach activity. We would also like to acknowledge the support of SBILab, Deptt of ECE, Centre of Excellence in Healthcare, IIIT-Delhi and the Infosys Centre for AI, IIIT-Delhi.
Pre-Requisites
- » Machine learning
- » OOPs
- » Python
- » Basic Programing skills
Schedule
Theory - Introduction to ML, DL, CNNs, and Image Segmentation
9:30 - 11:00 - Introduction to Machine Learning and Deep Learning Concepts
11:00 - 11:30 - Refreshments
11:30 - 1:00 - Introduction to Convolutional Neural Network (CNN) and Various CNN-Based Models.
1:00 - 2:00 - Lunch
Practical - Foundations of PyTorch
2:00 - 3:30 - PyTorch Basics, Tensors, Autograd
3:30 - 4:00 - Tea Break
4:00 - 5:30 - Data Utilities, Custom Data Loaders
Theory - Deep Learning Models for Image Segmentation
9:30 - 11:00 - Fully Convolutional Networks, Unet and Its Variants.
11:00 - 11:30 - Refreshments
11:30 - 1:00 - Segnet, U-Segnet, DeepLab and Its Variants
1:00 - 2:00 - Lunch
Practical - Neural Networks and Introduction to Image Segmentation
2:00 - 3:30 - Neural Networks, U-Net implementation
3:30 - 4:00 - Tea Break
4:00 - 5:30 - Evaluation Metrics
Theory - Introduction to Mask R-CNN and Variants
9:30 - 11:00 - R-CNN, Fast-RCNN, Faster-RCNN.
11:00 - 11:30 - Refreshments
11:30 - 1:00 - Mask-RCNN and its Applications and Variants of Mask R-CNN
1:00 - 2:00 - Lunch
Practical - Instance Segmentation and Model Implementation
2:00 - 3:30 - Mask R-CNN Concepts
3:30 - 4:00 - Tea Break
4:00 - 5:30 - Mask R-CNN Implementation and fine-tuning
Theory - Introduction to YOLO and Its Variants
9:30 - 11:00 - YOLO (Basic and Evolution)
11:00 - 11:30 - Refreshments
11:30 - 1:00 - Recent methods in YOLO
1:00 - 2:00 - Lunch
Practical - Deep Dive into YOLO
2:00 - 3:30 - YOLO overview and architecture
3:30 - 4:00 - Tea Break
4:00 - 5:30 - YOLO setup and training
Theory - Semi-Supervised Learning in Image Segmentation
9:30 - 11:00 - Semi-Supervised Learning (Concepts, applications and
techniques)
11:00 - 11:30 - Refreshments
11:30 - 1:00 - Future trends and open questions
1:00 - 2:00 - Lunch
Practical - Small Assessment/Hackathon
2:00 - 3:30 - Consolidate Learnings
3:30 - 4:00 - Tea Break
4:00 - 5:30 - Small Hackathon/Challenge
Registration
Step 1: Pay Here 
Step 2: Register Here
Registration Fee: INR 200 + 18% GST
NOTE:
- » Lunch can be availed from the college canteen on a paid basis**
- » Participants who attend at least 3 days of the workshop will be given participation certificates.
- » The participation certificate will clearly mention the participant's mode of attendance (online/offline).
Workshop Organizer
Prof. Anubha Gupta
Coordinators
Jivitesh Sabharwal
Anish Jain