In this blog post, we will be fine tuning the YOLOv7 object detection model on a real-world pothole detection dataset. Since its inception, the YOLO family of object detection models have come a ...
YOLOv7 is the new state-of-the-art object detector in the YOLO family. According to the paper, it is the fastest and most accurate real-time object detector to date. According to the YOLOv7 paper, the ...
In this blog post, we will be training YOLOv4 object detection model on a pothole detection dataset using the Darknet framework. Before we move further into the blog post, let’s have an overview ...
In this blog post, we are fine tuning YOLOv5 models for custom object detection training and inference. IntroductionWhat is YOLOv5?Models Available in YOLOv5Features Provided by YOLOv5Custom ...
The Intel-OpenVINO Toolkit provides many great functionalities for Deep-Learning model optimization, inference and deployment. Perhaps the most interesting and practical tool among them is the ...
Traditionally, Deep-Learning models are trained on high-end GPUs. But for inference, Intel CPUs and edge devices like NVidia’s Jetson and Intel-Movidius VPUs are preferred. Most of these Intel CPUs ...
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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.
