Machine Learning for computer vision

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Principal Coordinator :
  • Prof. Aparajita Ojha, IIITDM Jabalpur
  • Co-Principal Coordinator :
  • Dr. Santosh Vipparthi, MNIT Jaipur
  • Prof. Amey Karkare,IIT Kanpur
  • Dr Prthwijit Guha IIT Guwahati
  • Dr. Mukesh Kumar NIT Patna

  • Academy Level Coordinator:

    Dr. Somaraju Suvvari, NIT Patna
    Email: somaraju@nitp.ac.in
    Contact: 9676430356


    Course Fee Details:


    Academic (student/faculty): 500 INR
    Industry People/ Others : 1000 INR
    Foreign Participants: 4000 INR

    Payment Details:
    Bank Name: Allahabad Bank (Merge to Indian Bank)
    Account Name: NIT Patna
    Account No.: 50380476798
    IFSC Code: IDIB000B810


    Resource Persons:

    Prof. Shantanu Chaudhury, Director IIT Jodhpur; Dr. Suresh Sundaram, IITG; Prof. H. Fujiyoshi, Chubu Univ. Japan; Prof. Barbara Zitova, Acad Sci. Czech Repulic; Dr. Amit Sethi, IITB; Prof. Sumantra Dutta Roy, IITD; Prof. P. Guha, , Prof. Aparajita Ojha, IIITDM Jabalpur, Dr. Santosh Viparthi, MNIT Jaipur


    Course contents:


    S.No. Topics
    1 Introduction to Image Processing and Computer Vision (CV) Digital Image and Computer Vision, Main Goals and challenges of the CV, Structure of Human Eye and Vision, Color Models, Image Processing Goals and Tasks.
    2 Traditional approaches in CV Feature Extraction using local patterns and their applications to Image Processing and CV: SIFT, HOG, LBP, Natural Image Classification, Image Enhancement, edge Detection, Segmentation. Image denoising
    3 Introduction to Artificial Intelligence (AI) and Machine Learning (ML) AI and ML, Supervised and Unsupervised Learning, Traditional ML approaches,
    4 Neural Network as a learning machine, Machine learning. applications in computer vision. Image classification, Image segmentation etc
    5 Applications of ML in Medical Images Challenges in Medical image processing, ML for Medical Image processing, Medical image segmentation, classification and survival prediction, Medical image denoising, Medical image retrieval
    6 Introduction to Deep Learning (DL) Basic differences between Conventional ML and DL approaches, Feed forward Neural Networks (NN), Back propagation, Stochastics gradient method and variants, regularization,
    7 and optimization, Vanishing /exploding gradient problem.
    8 Introduction to Convolutional Neural Network The Convolution Operation, Basic architecture of a Convolution Neural Network, Pooling and Batch Normalization layers, CNNs as feature extractors, Image classification using CNN, Image Enhancement and Segmentation.
    9 CNN architectures for CV State of the Art CNN Architectures, CNN for Image Enhancement and Segmentation.
    10 Applications of CNN in face recognition Face Detection and Recognition using CNN, Siamese Network and Triplet Loss.

    Core Team Members, E&ICT Academy, NIT Patna:

    Dr. Bharat Gupta( CI E & ICT Academy,NIT Patna)
    Email: bharat@nitp.ac.in

    Dr. MP Singh ( CI E & ICT Academy,NIT Patna)
    Email: mps@nitp.ac.in

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



    Contact us :
    Electronics and ICT Academy
    National Institute of Technology, Patna
    AshokRajpath, Patna 800005
    Email: eictapatna@nitp.ac.in
    Website: http://old.nitp.ac.in/ict