DeepLearning-Wiki

이론으로 배운 딥러닝 모델을 직접 실습해본 저장소입니다. 특정 사이트에서 참고하여 가져온 소스코드의 경우에는, 링크로 표기해놓았으니 참고해주시기 바랍니다.

Object Detection

labelImg

• labelImg : Labeling Tool for Object Detection

YOLOv5

• YOLOv5 : 1-stage Object Detection

DETR

• DETR : Object Detection + Transformer
• DETR 코드리뷰

OCR-RCNN-V2

• [paper] OCR-RCNN: An Accurate and Efficient Framework for Elevator Button Recognition
• [github] OCR-RCNN-V2
• [Blog] Jetson TX2에서 OCR-RCNN-V2 실행시키기
• [Blog] [Ubuntu 16.04] OCR-RCNN-V2 실행
• [Blog] [Ubuntu 16.04] OCR-RCNN-V2 실행 에러

Semantic Segmentation

U-Net

• [Blog] U-Net 톺아보기(in-depth)
• [Blog] U-Net 실습
• Semantic Segmentation in Self-driving Cars.ipynb
• SIN-Segmentation

Generative Model

GAN

• GAN.ipynb

NLP (Natural Language Processing)

Sequence-to-Sequence

• seq2seq_tf.ipynb

GNN (Graph Neural Network)

GCN

• GCNLayer.ipynb

Transfer Learning

• Transfer-Learning.ipynb
• [Blog] Transfer Learning(전이학습) 톺아보기

XAI (Explanable AI)

SHAP (SHapley Additive exPlanation)

• SHAP practice with HTO custom dataset
• Using SHAP Values to Explain How Your Machine Learning Model Works
• (Explainable AI) SHAP에 대해 알아보자!
• An Overview of Model-Agnostic Interpretation Methods