Notice
Recent Posts
Recent Comments
Link
| 일 | 월 | 화 | 수 | 목 | 금 | 토 |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| 9 | 10 | 11 | 12 | 13 | 14 | 15 |
| 16 | 17 | 18 | 19 | 20 | 21 | 22 |
| 23 | 24 | 25 | 26 | 27 | 28 |
Tags
- dfs
- image processing
- C++
- CNN
- 머신러닝
- two-stage detector
- 딥러닝
- real-time object detection
- DP
- Mask Processing
- opencv
- deep learning
- YoLO
- 백준
- LSTM
- r-cnn
- machine learning
- 그래프 이론
- MinHeap
- BFS
- AlexNet
- 강화학습
- MySQL
- canny edge detection
- dynamic programming
- One-Stage Detector
- object detection
- Reinforcement Learning
- Python
- eecs 498
Archives
- Today
- Total
목록dense evaluation (1)
JINWOOJUNG
Very Deep Convolutional Networks for Large-Scale Image Recognition...(1)
Research Paperhttps://arxiv.org/abs/1409.1556https://papers.nips.cc/paper_files/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.htmlhttps://www.researchgate.net/publication/220812758_Flexible_High_Performance_Convolutional_Neural_Networks_for_Image_Classification0. Abstract본 논문에서는 Convolutional Network의 Depth에 따른 성능을 분석한다. 3x3의 작은 Convolutional Filter를 사용하여 Network의 Depth를 16~19까지 증가시킴..
딥러닝/논문
2025. 1. 7. 11:42