Object detection is a key area in computer vision, and YOLOv2 is a powerful tool used for this purpose. YOLOv2 stands for You Only Look Once version 2, and is an improved version of the earlier YOLOv1.
What is Object Detection?
Object detection is the process of identifying objects in images or videos and accurately placing a bounding box around them. This is a crucial task for many applications such as self-driving cars, surveillance systems, and augmented reality.
What is YOLOv2?
YOLOv2
YOLOv3 is an advanced object detection model that is designed to detect objects in real-time. It is a single-stage model that has made significant improvements over YOLOv2. The model is built on a new backbone network, Darknet-53, which uses residual connections to improve performance. Additionally, YOLOv3 uses three different scales from which it extracts features, allowing it to provide better object detection results.
What is Object Detection?
Object detection is a computer vision techniqu
YOLOv4: The Latest Advancement in Object Detection Model
When it comes to detecting objects in images, YOLOv4 is the latest state-of-the-art model that is taking the field by storm. Building on the success of the previous version, YOLOv3, this new model includes various bags of tricks and modules to improve its performance and accuracy.
What is Object Detection?
Object detection is a computer vision technique that aims to find and identify objects within an image or video. It is a challengin
YOLOX is an object detector that has been making several modifications to YOLOv3 with a DarkNet53 backbone. This modified detector has been altered for better performance by replacing the head with a decoupled one, reducing feature channel and adding two parallel branches. Moreover, it has added Mosaic and MixUp into the augmentation strategies to enhance performance. This article will explore further the modifications of the YOLOX detector alongside its features.
YOLOX Features
The YOLOX det