YOLO
Real-time object detection
YOLO launched on January 22, 2018 with 16 votes, #971 of 3,022 launches that month and more than 50% of that year's launches. The site was still online in September 2026, 8 years on.
What it does
You only look once (YOLO) is a state-of-the-art, real-time object detection system. On a Pascal Titan X it processes images at 30 FPS and has a mAP of 57.9% on COCO test-dev. YOLOv3 is extremely fast and accurate. In mAP measured at .5 IOU YOLOv3 is on par with Focal Loss but about 4x faster. Moreover, you can easily tradeoff between speed and accuracy simply by changing the size of the model, no retraining required! 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…from pjreddie.com
Does a similar job
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Real-Time YOLO Object Detection in Elixir: Fast, Simple, Extensible2024 · github.com · ▲96A library for object detection and seamless YOLO model integration in Elixir - poeticoding/yolo_elixir
- UYUsing YOLO to Detect Office Chairs in 40M Hotel Photos2025 · ▲222
I used the YOLO object detection library from Ultralytics to scan over 40 million hotel photos and identify images with office chairs. This helped me create a map showing hotels suitable for remote work. Map: https://www.tripoffice.com/maps Yolo: https://www.ultralytics.com/yolo The whole process was done on a home Mac without the use of any LLMs. It's based on traditional object detection technology.
- UDUsing deep learning to detect objects from your webcam2018 · modeldepot.github.io · ▲95
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