{"action":"created","comment":{"url":"https://api.github.com/repos/vitalab/vitalab.github.io/pulls/comments/103567348","pull_request_review_id":24347904,"id":103567348,"diff_hunk":"@@ -0,0 +1,52 @@\n+\n+\n+```\n+---\n+layout: review\n+title:  You Only Look Once: Unified, Real-Time Object Detection (YOLO)\n+author: Frédéric Branchaud-Charron\n+link:   https://arxiv.org/abs/1506.02640\n+tags:   convolutional-networks deep-learning object-detection bounding-boxes\n+---\n+```\n+\n+YOLO v1\n+\n+## Summary\n+\n+**YOLO** is an unified solution to the object detection problem. Other approches like **R-CNN** are using a two step process *(localization and classification)* where **YOLO** is a one step process. Also, **Fast YOLO** (or tiny-yolo) is achieving of 155 fps where **Faster R-CNN** is doing 18 fps.\n+\n+On the Pascal VOC-2012 dataset, **YOLO** is achieving 63.4 mAP where **Faster R-CNN** is doing 73.2. In this case, **Faster R-CNN** is not real-time (7 fps) while **YOLO** is doing around 60 fps.\n+\n+It's important to know that **YOLO** only support a **single** aspect ratio, this is fixed in **YOLOV2** and this is the main drawback if we compare **YOLOV1** to Single shot detector (**SSD**)","path":"deep-learning/_papers/2017-02-28-you-only-look-once.md","position":21,"original_position":21,"commit_id":"e1ed9a163edccc61560f1b1cf94cf0ac02e533f7","original_commit_id":"e1ed9a163edccc61560f1b1cf94cf0ac02e533f7","user":{"login":"lemairecarl","id":13444373,"avatar_url":"https://avatars0.githubusercontent.com/u/13444373?v=3","gravatar_id":"","url":"https://api.github.com/users/lemairecarl","html_url":"https://github.com/lemairecarl","followers_url":"https://api.github.com/users/lemairecarl/followers","following_url":"https://api.github.com/users/lemairecarl/following{/other_user}","gists_url":"https://api.github.com/users/lemairecarl/gists{/gist_id}","starred_url":"https://api.github.com/users/lemairecarl/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/lemairecarl/subscriptions","organizations_url":"https://api.github.com/users/lemairecarl/orgs","repos_url":"https://api.github.com/users/lemairecarl/repos","events_url":"https://api.github.com/users/lemairecarl/events{/privacy}","received_events_url":"https://api.github.com/users/lemairecarl/received_events","type":"User","site_admin":false},"body":"support a --> support**s** a\r\n\r\nAlso, I don't understand the sentence. Is the aspect ratio fixed in both versions of YOLO 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