[1일차] Pixel Data 처리를 위한 Image Processing

- Image Processing Fundametals
- Image Coordinate System
- Scaling and Aspect Ratios
- Image Classification

[2일차] 시간인지를 위한 딥러닝

- Deep Learning Classification Pipeline
- Optimization Methods and Regularization
- Learning Rate Schedulers
- Spotting Underfitting and Overfitting
- Visualizing Network Architectures
- CNNs for Classification

[3일차] 딥러닝 시가인지 아카텍쳐 이해

- Data Augmentation
- Networks as Feature Extractors
- Ranked Accuracy / Fine-tuning Networks
- Advanced Optimization Methods
- AlexNet / VGGNet / GoogLeNet / ResNet

[4일차] 딥러닝 기반 영상처리 실무

- 이미지 탐색 알고리즘
- R-CNN / You Only Look Once
- AttentionNet
- 시각인지(Visualizing and Understanding)
- 시각적 특징 및 반전(Feature visualization and inversion)
- 적대적 예시(Adversarial examples)