In deep learning, training a model is not the final step. Be it image classification or object detection, a deep learning project becomes worthwhile only when it reaches the masses. That's where ...
Ultralytics recently released the YOLOv8 family of object detection models. These models outperform the previous versions of YOLO models in both speed and accuracy on the COCO dataset. But what about ...
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. ...
DeepLab models, first debuted in ICLR ‘14, are a series of deep learning architectures designed to tackle the problem of semantic segmentation. After making iterative refinements through the years, ...
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. ...
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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.
