Syllabus

Note: The detailed course material can be modified.

For the Cont. case, we will use the slides from the previous lecture.

Lecture - 1. Tuesday: Introduction, supplementary material: git textbook, git basics part1, part2

Lecture -1. Thursday: Color, Pixel, and Linear Algebra, Self-study material 

• Note: Equations in slide 71 modified. Thank you for the correction!

Lecture - 2. Tuesday: Linear Algebra review - part1.  Self-study material

• Don't worry, we won't cover everything on the slide. 

Lecture - 2. Thursday:  Linear Algebra review part2. + Filter and Convolution - 1, 

Lecture- 3. Tuesday: Filters and Convolution.2. . Self-study material

Lecture- 3. Thursday: Filters and Convolution Cont. + Edge detection, Self-study material

Lecture- 4. Tuesday: Feature Descriptors 1&2. Self-study material

Lecture- 4. Thursday: Feature Descriptors.cont 

Lecture- 5. Tuesday: Panorama 1, 

Lecture- 5. Thursday: Panorama 1. + Filter and Convolution - 1,  Filters and Convolution.2.

Lecture-6. Tuesday:   Edge detection

Lecture-6. Thursday: Edge detection, Feature Descriptors 1&2

Lecture-7. Tuesday: Panorama (Short) + Discussions in Issue

Lecture-7. Thursday: Research Talk 1 - Dongyoon Han. Leader@NAVER AILAB

Lecture-8. Tuesday: Self-study

Lecture-8. Thursday: Midterm

Lecture-9. Tuesday: Object Recognition- Intro, KNN, Over/Underfitting 

Lecture-9. Thursday: Object Recognition, Convolutional neural network, Pooling

Lecture-10. Tuesday:  Object Recognition, Convolutional Neural Network, Activation, Optimization

Lecture-10. Thursday:  Object Recognition, Activation, Optimization, Regularization, Network Introductions (1)

Lecture-11. Tuesday: Off

Lecture-11. Thursday: Regularization, Network Introduction (2) - AlexNet, GoogleNet, VGGNet, and ResNet

Lecture-12. Tuesday:  ResNet and Lightweight Networks: MobileNet v1&v2

Lecture-12. Thursday: Object Detection, Basics, RCNN, Fast RCNN

Lecture-13. Tuesday: Object Detection: Faster RCNN, YoLO, Single shot Multibox Detector

Lecture-13. Thursday: SSD,  Semantic / Instance Segmentation

Lecture-14. Tuesday: Very brief introduction of changes after Transformer 

Lecture-14. Thursday: Memorial day

Lecture-15. Tuesday: Wrap up

Lecture-15. Thursday: Research talk 2 - Sangdoo Yun, Research Head@NAVER AILAB

Lecture-16. Tuesday: Wrap up

Lecture-16. Thursday: Final Exam