This study evaluates YOLOv12 using a globally sourced traffic dataset that includes varied weather conditions, lighting scenarios, and geographic locations. The model demonstrates strong performance ...

The problem discussed in this article is object detection using deep neural network especially convolution neural networks. Object detection was previously done using only conventional deep ...

FLS image object detection (Karimanzira et al., 2020) refers to using computer vision and signal processing technology to perform object detection and recognition on the image data obtained by sonar ...

To address these issues, we propose MAFF-Net, a novel multi-assist feature fusion network specifically designed for 3D object detection using a single 4D radar. We introduce a sparsity pillar ...

YouTube Testing Google Lens Button With Object Detection, OCR-Based Search on Android: Report Users will reportedly be able to capture objects and search for related content around them on YouTube for ...

In recent decades, image processing and computer vision models have played a vital role in moving object detection on the synthetic aperture radar (SAR) images. Capturing of moving objects in the SAR ...

With the progress of deep learning, significant advancements have been made in solving computer vision tasks such as object detection and semantic segmentation. However, in real-world scenarios like ...

SynthDet is an open source project that demonstrates an end-to-end object detection pipeline using synthetic image data. The project includes all the code and assets for generating a synthetic dataset ...