You only look once (YOLO) is a state-of-the-art, real-time object detection system. YOLO: Real-Time Object Detection. Prior detection systems repurpose classifiers or localizers to perform detection. They apply the model to an image at multiple locations and scales. High scoring regions of the image are considered detections. We use a totally different approach. We apply a single neural network to the full image. This network divides the image into regions and predicts bounding boxes and probabilities for each region. These bounding boxes are weighted by the predicted probabilities. Our model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image. It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. This makes it extremely fast, more than 1000x faster than R-CNN and 100x faster than Fast R-CNN. See our paper for more details on the full system.
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References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
- Tianming Liu, Haoyu Wang, Li Li, Xiapu Luo, Feng Dong, Yao Guo, Liu Wang, Tegawendé F. Bissyandé, Jacques Klein: MadDroid: Characterising and Detecting Devious Ad Content for Android Apps (2020) arXiv
- Rajan, Purnima; Ma, Yongming; Jedynak, Bruno: Cox processes for counting by detection (2019)
- Wang, Sen; Xing, Yuxiang; Zhang, Li; Gao, Hewei; Zhang, Hao: Deep convolutional neural network for ulcer recognition in wireless capsule endoscopy: experimental feasibility and optimization (2019)
- Maxime Rousseau; Jean-Marc Retrouvey: pfla: A Python Package for Dental Facial Analysis using Computer Vision and Statistical Shape Analysis (2018) not zbMATH
- Tsai, Chi-Yi; Hsu, Kuang-Jui; Nisar, Humaira: Efficient model-based object pose estimation based on multi-template tracking and PnP algorithms (2018)
- Zhang, Jianming; Huang, Manting; Jin, Xiaokang; Li, Xudong: A real-time Chinese traffic sign detection algorithm based on modified YOLOv2 (2017)
Further publications can be found at: https://pjreddie.com/publications/