[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) 