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Lec 35 : Artificial Neural Network for Pattern Classification - I
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Classroom Contents
Computer Vision and Image Processing - Fundamentals and Applications
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- 1 Computer Vision and Image Processing – Fundamentals and Applications [Intro Video]
- 2 Lec 1 : Introduction to Computer Vision
- 3 Lec 2 : Introduction to Digital Image Processing
- 4 Lec 3 : Image Formation: Radiometry
- 5 Lec 4 : Shape From Shading
- 6 Lec 5 : Image Formation: Geometric Camera Models - I
- 7 Lec 6 : Image Formation: Geometric Camera Model - II
- 8 Lec 7 : Image Formation: Geometric Camera Model - III
- 9 Lec 8 : Image Formation in a Stereo Vision Setup
- 10 Lec 9 : Image Reconstruction from a Series of Projections
- 11 Lec 10 : Image Reconstruction from a Series of Projections
- 12 Lec 11 : Image Transforms - I
- 13 Lec 12 : Image Transforms - II
- 14 Lec 13 : Image Transforms - III
- 15 Lec 14 : Image Transforms - IV
- 16 Lec 15 : Image Enhancement.
- 17 Lec 16 : Image Filtering-I
- 18 Lec 17 : Image Filtering-II
- 19 Lec 18 : Colour Image Processing - I
- 20 Lec 19 : Colour Image Processing - II
- 21 Lec 20 : Image Segmentation
- 22 Lec 21 : Image Features and Edge Detection
- 23 Lec 22 : Edge Detection
- 24 Lec 23 : Hough Transform
- 25 Lec 24 : Image Texture Analysis - I
- 26 Lec 25 : Image Texture Analysis - II
- 27 Lec 26 : Object Boundary and Shape Representations - I
- 28 Lec 27 : Object Boundary and Shape Representations - II
- 29 Lec 28 : Interest Point Detectors
- 30 Lec 29 : Image Features - HOG and SIFT
- 31 Lec 30 : Introduction to Machine Learning - I
- 32 Lec 31 : Introduction to Machine Learning - II
- 33 Lec 32 : Introduction to Machine Learning - III
- 34 Lec 33 : Introduction to Machine Learning - IV
- 35 Lec 34 : Introduction to Machine Learning - V
- 36 Lec 35 : Artificial Neural Network for Pattern Classification - I
- 37 Lec 36 : Artificial Neural Network for Pattern Classification - II
- 38 Lec 37 : Introduction to Deep Learning
- 39 Lec 38 : Gesture Recognition
- 40 Lec 39 : Background Modelling and Motion Estimation
- 41 Lec 40 : Object Tracking
- 42 Lec 41 : Programming Examples
