What is YOLOv8? YOLOv8 is the latest family of YOLO based Object Detection models from Ultralytics providing state-of-the-art performance. Leveraging the previous YOLO versions, the YOLOv8 ...
The YOLOv5 object detection models are well known for their excellent performance and optimized inference speed. Recently the support for instance segmentation has also been added to the codebase. ...
If you are undertaking an object detection project, the probability is high that you would choose one of the many YOLO models. Going by the number of YOLO object detection models out there, it's a ...
FCOS: Fully Convolutional One-stage Object Detection is an anchor-free (anchorless) object detector. It solves object detection problems in a per-pixel prediction fashion, similar to segmentation. ...
Anchor free object detection is powerful because of its speed and generalizability to other computer vision tasks. "CenterNet: Object as Points" is one of the milestones in the anchor-free object ...
Arguably, the most crucial task of a Deep Learning based Multiple Object Tracking (MOT) is not to identify an object, but to re-identify it after occlusion. There are a plethora of trackers available ...
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In 2007, right after finishing my Ph.D., I co-founded TAAZ Inc. with my advisor Dr. David Kriegman and Kevin Barnes. The scalability, and robustness of our computer vision and machine learning algorithms have been put to rigorous test by more than 100M users who have tried our products.
