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. ...
YOLOv6 Custom Dataset Training – Underwater Trash Detection
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 ...
YOLOv6 Object Detection – Paper Explanation and Inference
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 ...
Fine Tuning YOLOv7 on Custom Dataset
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 ...
YOLOv7 Object Detection Paper Explanation & Inference
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 ...
YOLOv4 and Darknet For Pothole Detection
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 ...
