YOLO-NAS Pose models is the latest contribution to the field of Pose Estimation. Earlier this year, Deci garnered widespread recognition for its groundbreaking object detection foundation model, ...
Comparing KerasCV YOLOv8 Models on the Global Wheat Data 2020
This article is a continuation of our series of articles on KerasCV. The previous article discussed fine-tuning the popular DeeplabV3+ model for semantic segmentation. In this article, we will shift ...
Animal Pose Estimation: Fine-tuning YOLOv8 Pose Models
Animal pose estimation is an area of research within computer vision, a subfield of artificial intelligence, focused on automatically detecting and analyzing the postures and positions of animals in ...
Weighted Boxes Fusion in Object Detection: A Comparison with Non-Maximum Suppression
Weighted box fusion: The post-processing step is a trivial yet important component in object detection. In this article, we will demonstrate the significance of Weighted Boxes Fusion (WBF) as opposed ...
Train YOLO NAS on Custom Dataset
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 ...
Train YOLOv8 Instance Segmentation on Custom Data
Image segmentation is a core vision problem that can provide a solution for a large number of use cases. Starting from medical imaging to analyzing traffic, it has immense potential. Instance ...
