Machine Learning for Computer Vision


Resource Persons:

  • Prof. P.K. Biswas, IIT Kharagpur
  • Dr. Partha Pratim Roy, IIT Roorkee
  • Dr. Santosh Viparthi, MNIT Jaipur
  • Prof. Aparajita Ojha, IIITDM Jabalpur
  • 1 full day session by an expert from NVIDIA

Principal Coordinator :
  • Prof. Aparajita Ojha, IIITDM Jabalpur
Principal Co-coordinator :
  • Dr. Santosh Kumar Vipparthi ,MNIT, Jaipur

June 29 - July 10 , 2020

Brochure

Apply Online


Academy Level Coordinator:

Dr. Mukesh Kumar
Email: mukesh.kumar@nitp.ac.in
Contact: 8984142557

Dr. Subodh Srivastava
Email: subodh@nitp.ac.in
Contact: 8090318878


Course Fee Details:


Academic (student/faculty): 500 INR (GEN/OBC) / 250 INR (SC/ST)
Industry People/Others : 1000 INR/ 500INR (SC/ST)

Payment Details:
Bank Name: Allahabad Bank
Account Name: NIT Patna
Account No.: 50380476798
IFSC Code: ALLA0212286


Course contents:


S.No. Module Name Topics
1 Introduction to Image Processing and Computer Vision (CV) Introduction to Computer Vision, Main Goals and Challenges, Structure of Human Eye and Vision, Color Models, Image Processing Goals and Tasks, Image Enhancement, Edge Detection, Segmentation
2 Introduction to Artificial Intelligence (AI) and Machine Learning (ML) Introduction to Artificial Intelligence and Machine Learning, Supervised and Unsupervised Learning, Feature Extraction using Local Patterns and their applications to Image Processing and CV: Image Classification, Image Enhancement, Segmentation.
3 Introduction to Deep Learning (DL) Basic differences of Conventional ML and DL approaches, Feed forward Neural Networks (NN), Back propagation, Stochastics Gradient Method and Variants, Regularization, and Optimization. Types of NNs and limitations. Applications of NN in Image Processing and CV.
4 Convolutional Neural Network architectures (CNN) for CV The Convolution Operation, Motivation, Pooling, Basic architecture of a Convolution Neural Network CNN as feature extractors, Image classification using CNN, Image Enhancement and Segmentation, Introduction to GAN
5 Motion Detection and Depth Estimation (DE) Optical Flow, Flow Net and their Versions, Stereo Vision, DL based Depth Estimation
6 Object Detection using CNN R-CNN, Faster R-CNN, YOLO, SSD and more recent models for Object Detection.
7 Applications of CNN Face Detection and Recognition using CNN, Siamese Network and Triplet Loss. Recent Advances

Core Team Members, E&ICT Academy:

Dr. MP Singh
Email: mps@nitp.ac.in

Dr. Bharat Gupta
Email: bharat@nitp.ac.in

Website: http://old.nitp.ac.in/ict/index.php