RF-DETR is a real-time, transformer-based object detection model architecture developed by Roboflow and released under the Apache 2.0 license. RF-DETR is the first real-time model to exceed 60 AP on ...
Abstract: Out-of-distribution (OoD) inputs pose a persistent challenge to deep learning models, often triggering overconfident predictions on non-target objects. While prior work has primarily focused ...
Physically, sound is just pressure moving through a medium. If you harness that pressure correctly, you can actually push things around using nothing but sound. That's exactly what researchers at ...
A high-performance, privacy-first web application for real-time object detection that runs entirely in your browser using WebGPU acceleration and ONNXRuntime-Web. No server required, no data leaves ...
The risk of fires in both indoor and outdoor scenarios is constantly rising around the world. The primary goal of a fire detection system is to minimize financial losses and human casualties by ...
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 ...
Introduction: Accurate vehicle analysis from aerial imagery has become increasingly vital for emerging technologies and public service applications such as intelligent traffic management, urban ...
Abstract: Accurate and efficient small object detection using multimodal remote sensing images on resource-constrained aerial platforms is a challenging task. Most existing solutions rely on complex ...
Realtime Robotics, a provider of robotic motion-planning software, today released two new direct integrations for Resolver. The company said Resolver is a cloud-based system that can accelerate the ...
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