반응형
250x250
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 | 29 | 30 |
Tags
- 객체 검출
- polling-based object probing evaluation
- 에지 검출
- 이미지 필터링
- dinov2 논문 리뷰
- Object detection article
- dinov2: learning robust visual features without supervision 논문 리뷰
- 논문 리뷰
- 원격 학습 안끊기게
- object detection
- evaluating object hallucination in large vision-language models 논문
- evaluating object hallucination in large vision-language models paper
- vlm 환각
- evaluating object hallucination in large vision-language models
- mobilenetv1
- dinov2: learning robust visual features without supervision 논문
- 딥러닝 엔트로피
- 딥러닝 목적함수
- clip
- 기계학습
- vlm 환각이란
- vlm hallucination
- 1차 미분 마스크
- vlm hallucination paper
- blip-2
- vlm
- 엔트로피란
- clip adapter
- 논문 요약
- dinov2: learning robust visual features without supervision
Archives
- Today
- Total
목록Fast R-CNN (1)
My Vision, Computer Vision
[논문 리뷰/요약]Fast R-CNN
Fast R-CNN This paper proposes a Fast Region-based Convolutional Network method (Fast R-CNN) for object detection. Fast R-CNN builds on previous work to efficiently classify object proposals using deep convolutional networks. Compared to previous work, Fast R-CNN emp arxiv.org Abstract Fast R-CNN(Region-based)은 R-CNN에 비해 VGG16을 9배 빠르게 훈련시키고, test time은 213배 더 빠르다. PASCAL VOC 2012에서 높은 mAP 성능을 달성..
Paper
2024. 2. 9. 21:03