This course offers fundamental concepts in computer vision. Being an introduction to the common terminology and basic applications of computer vision, the aim of this course is to let students gain fundamental computer vision techniques and apply them to basic problems.
Syllabus
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1 |
Introduction to Computer Vision |
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2 |
Matlab Fundamentals |
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3 |
Image Formation |
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4 |
Filtering, Edge Detection |
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5 |
Hough Transform |
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6 |
FFT |
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7 |
Morphological Image Processing |
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8 |
Features, SIFT, Viola Jones |
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9 |
Camera Fundamentals, Calibration |
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10 |
Feed Forward Neural Networks |
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11 |
Learning Based Vision, Deep Learning Fundamentals |
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12 |
CNN Architectures,Transfer Learning |
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13 |
SSD,R-CNN, Object Detection |
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14 |
Semantic Segmentation |