Indian Institute of Information Technology, Allahabad

Computer Vision and Biometrics Lab (CVBL)

Deep Learning

July-Dec 2021 Semester


Course Information

Objective of the course: To get the students and researchers exposed to the state-of-the-art deep learning techniques, approaches and how to optimize their results to increase its efficiency and get some hands-on on the same to digest the important concepts.

Outcome of the course: As deep learning has demonstrated its tremendous ability to solve the learning and recognition problems related to the real world problems, the software industries have accepted it as an effective tool. As a result there is a paradigm shift of learning and recognition process. The students and researchers should acquire knowledge about this important area and must learn how to approach to a problem, whether to deal with deep learning solution or not. After undergoing this course they should be able to categorize which algorithm to use for solving which kind of problem. Students will be able to find out the ways to regularize the solution better and optimize it as per the problem requirement. Students will be exposed to the background mathematics involved in deep learning solutions. They will be able to deal with real time problems and problems being worked upon in industries. Taking this course will substantially improve their acceptability to the machine learning community – both as an intelligent software developer as well as a matured researcher.



Class meets
Monday: 08.00 am - 10.00 am, Tuesday: 06.00 pm - 08.00 pm, Thursday 10.00 am - 12.00 pm; Remote

Schedule - Lectures

Date Topic Optional Reading
L01: August 02: 08.00 AM - 09.00 AM Introduction Lecture: Linear Machines and Learning
Slide, Recorded Video
L02: August 02: 09.00 AM - 10.00 AM Supervised Learning Algorithms
Slide, Recorded Video
L03: August 05: 10.00 AM - 12.00 PM Linear Classifiers
Slide, Recorded Video
L04: August 09: 08.00 AM - 10.00 AM Support Vector Machines
Slide, Recorded Video
L05-06: August 16: 08.00 AM - 10.00 AM Neural Networks and Pre-Deep Learning Essentials
Slide, Recorded Video
L07-08: August 24: 06.00 PM - 08.00 PM Deep Learning: Introduction, Motivation and Status
Slide, Recorded Video1 Recorded Video2
L09: August 26: 10.00 AM - 11.00 AM Convolutional Neural Networks
Slide, Recorded Video
L10: August 30: 08.00 AM - 09.00 AM CNN Essentials
Slide, Recorded Video
L11: August 30: 09.00 AM - 10.00 AM CNN Performance
Slide, Recorded Video
L12: September 02: 10.00 AM - 12.00 PM Activation Functions
Slide, Recorded Video
L13-14: September 06: 08.00 AM - 10.00 AM Loss Functions and Regularization
Slide, Recorded Video1 Recorded Video2
L15: September 07: 06.00 PM - 07.00 PM Transfer Learning
Slide, Recorded Video
L16-17: September 23: 10.00 AM - 12.00 PM CNN Architectures for Image Classification
Slide, Recorded Video
L18-19: September 27: 08.00 AM - 10.00 AM CNN Architectures for Object Detection
Slide, Recorded Video
L20-21: September 30: 10.00 AM - 12.00 PM CNN Architectures for Image Segmentation and Dense Prediction
Slide, Recorded Video
L22: October 11: 08.00 AM - 09.00 AM Adversarial Attack: Fooling Deep Learning Models
Slide, Recorded Video
L23-25: October 11: 09.00 AM - 10.00 AM & October 12: 06.00 PM - 08.00 PM Generative Adversarial Networks
Slide, Recorded Video(Oct 11), Recorded Video(Oct 12)
L26-28: October 21: 11.00 AM - 12.00 PM & October 28: 10.00 AM - 12.00 PM Recurrent Neural Networks
Slide, Recorded Video(Oct 21), Recorded Video(Oct 28)
    L29: October 24: 11.00 AM - 12.00 PM Special Lecture on Face Recognition under Surveillance by Dr. Satish Kumar Singh
    Lecture Slide
      L30: October 26: 06.00 PM - 07.00 PM Special Lecture on Biometric Security by Prof. Pritee Khanna (IIITDM Jabalpur)
      Recorded Video
        L31: October 26: 07.00 PM - 08.00 PM Special Lecture on DeepFakes by Dr. Kiran Raja (NTNU Norway)
        Recorded Video
          L32-33: October 27: 06.00 PM - 08.00 PM Special Lecture on Biometrics Recognition using Data Analytics and Predictive Technologies by Prof. Sanjay Kumar Singh (IIT BHU) and Deep Learning for 3D Biometric by Prof. Surya Prakash (IIT Indore)
          Recorded Video

            Schedule - Tutorials and Labs

            Date Topic Optional Reading
            TL01-02: July 27: 06.00 PM - 08.00 PM Introduction to Python
            Recorded Video
            TL03-04: July 29: 10.00 AM - 12.00 PM Introduction to Python
            Recorded Video
            TL05-06: August 03: 06.00 PM - 08.00 PM Introduction to Python
            Recorded Video
            TL07-08: August 10: 06.00 PM - 08.00 PM Project Discussions
            TL09-10: August 12: 10.00 AM - 12.00 PM Project Discussions
            TL11-12: August 17: 06.00 PM - 08.00 PM Project Discussions
            TL13-14: August 19: 10.00 AM - 12.00 PM Project Discussions
            TL15-16: Sept 28: 06.00 PM - 08.00 PM Project Discussions
            TL17-18: Oct 04: 08.00 AM - 10.00 AM Project Discussions
            TL19-20: Oct 05: 06.00 PM - 08.00 PM Project Discussions
            TL21-22: Oct 07: 10.00 AM - 12.00 PM Project Work
            TL23-24: Oct 18: 08.00 AM - 10.00 AM CRP2 Assessment
            TL25-26: Oct 21: 10.00 AM - 12.00 PM CRP2 Assessment

            Grading

            • C1 (30%): 10% Written + 20% Practice
            • C2 (30%): 10% Written + 20% Practice
            • C3 (40%): 20% Written + 20% Practice

            Prerequisites

            • Computer Programming
            • Data Structures and Algorithms
            • Machine Learning
            • Image and Video Processing
            • Ability to deal with abstract mathematical concepts

            Disclaimer

            The content (text, image, and graphics) used in this slide are adopted from many sources for Academic purposes. Broadly, the sources have been given due credit appropriately. However, there is a chance of missing out some original primary sources. The authors of this material do not claim any copyright of such material.