Archives for object detection
The new YOLO-NAS has better object detection capabilities and enhanced accuracy, outperforming competing notable models such as YOLOv6, v7 & v8.
The post YOLO-NAS Sets a New Standard for Object Detection appeared first on Analytics India Magazine.
YOLO v8 claims to be faster, precise for better object detection, image segmentation and classification.
The post Object Detection Gets a New Upgrade with YOLO v8 appeared first on Analytics India Magazine.
YOLO v8 claims to be faster, precise for better object detection, image segmentation and classification.
The post Object Detection Gets a New Upgrade with YOLO v8 appeared first on Analytics India Magazine.
STEGO nearly doubles in MIoU un both unsupervised as well as linear probe metrics in comparison to its predecessors.
ImageNet is a dataset of over 15 million labelled high-resolution images across 22,000 categories.
Object detection is a task that involves bounding boxes and classifying them into categories to locate all positions of objects of interest in an input.
Detic, like ViLD, uses CLIP embeddings as the classifier.
In this article, we will talk about how to segment images at the image level using the image-level supervision approach.
In this article, we will talk about ChainerCV, a library that has a variety of models that are required for computer vision-related tasks.
IceVision is a framework for object detection which allows us to perform object detection in a variety of ways using various pre-trained models provided by this framework. It also offers data curation features along with a dashboard for exploratory data analysis. The best feature it has is that it provides an end-to-end deep learning workflow…