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 ...
YOLO-NAS is currently the latest YOLO object detection model. From the outset, it beats all other YOLO models in terms of accuracy. The pretrained YOLO-NAS models detect more objects with better ...
Developing a new YOLO-based architecture can redefine state-of-the-art (SOTA) object detection by addressing the existing limitations and incorporating recent advancements in deep learning. Deep ...
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 ...
In recent years, we have seen tremendous progress in the YOLO series, now hosting both anchor-free and anchor-based object detection models. Instead of focusing solely on architectural changes, YoloR ...
Annotation is the most crucial part of a Deep Learning project. It is a deciding factor in how well a model learns. However, it is very tedious and time-consuming. One solution is to use an automated ...
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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.
