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 ...
What is YOLOv7? YOLOv7 is a single-stage real-time object detector. It was introduced to the YOLO family in July'22. According to the YOLOv7 paper, it is the fastest and most accurate real-time ...
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, let’s have an overview of the models that ...
In this blog post, we are fine tuning YOLOv5 models for custom object detection training and inference. Introduction The field of deep learning started taking off in 2012. Around that time, ...
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.
