Introduced in the paper "Roboflow 100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models", RF100-VL is a large-scale collection of 100 multi-modal datasets with diverse concepts ...

A fault detection method for power conversion circuits using thermal images and a convolutional autoencoder is presented. The autoencoder is trained on thermal images captured from a commercial power ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

Either way, let’s not be in denial about it. Credit...Illustration by Christoph Niemann Supported by By Kevin Roose and Casey Newton Kevin Roose and Casey Newton are the hosts of The Times’s “Hard ...

Abstract: Deep learning-based object detection research has primarily evolved around RGB camera imagery. While state-of-the-art models like YOLO, SSD, and RetinaNet demonstrate high accuracy in RGB ...

This flow automatically fetches NASA's Astronomy Picture of the Day (APOD) using a Raspberry Pi and GitHub Actions, then analyzes the image using MATLAB (or MATLAB Online).

Sonar image object detection plays a crucial role in obstacle detection, target recognition, and environmental perception in autonomous underwater vehicles (AUVs). However, the complex underwater ...

Weed management presents a major challenge to vegetable growth. Accurate identification of weeds is essential for automated weeding. However, the wide variety of weed types and their complex ...