Object detection and segmentation are two important tasks in computer vision that aim to locate and classify objects in an image or a video. They have many applications, such as face recognition ...

This project demonstrates object detection and instance segmentation with a Mask R-CNN using PyTorch and TorchVision. It fine-tunes a pre-trained Mask R-CNN model on the Penn-Fudan dataset, which ...

Computer vision is a crucial component of many modern businesses, including automobiles, robotics, and manufacturing, and its market is growing rapidly. This book helps you explore Detectron2, ...

The work is published in the journal CAAI Artificial Intelligence Research.. In computer vision research, image segmentation technology involves separating digital images into meaningful parts.

As a consequence, semantic segmentation does pixel-by-pixel classification, such as detecting whether a pixel belongs to a pedestrian, a car, or a traversable road. Image segmentation datasets. To ...

Semantic segmentation, which involves categorising each pixel in a high-resolution image to identify objects and potential obstructions, demands substantial computational resources, making real-time ...

Computer vision models are generally more complex because they detect objects and react to them not only in images, but videos & live streams as well. A computer vision model is generally a ...

A research team has developed a computer vision technique that can perform dichotomous image segmentation, high-resolution salient object detection, and concealed object detection in the same ...