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. ...
The field of object detection is coming across a new YOLO model release every few months. Although reading the paper should be the first step towards exploring the model, we can evaluate the model ...
YOLO models have become ubiquitous in the world of deep learning, computer vision, and object detection. If you are working on object detection, then there is a high chance that you have used one of ...
Since its inception, the YOLO family of object detection models has come a long way. YOLOv7 is the most recent addition to this famous anchor-based single-shot family of object detectors. It comes ...
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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.
