The U.S. Naval Research Laboratory (NRL) launched a remote sensing experiment to sharpen artificial intelligence (AI) ...
WASHINGTON – The U.S. Naval Research Laboratory (NRL) launched a remote sensing experiment to sharpen artificial intelligence ...
This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...
Abstract: Detecting oriented tiny objects, which are limited in appearance information yet prevalent in real-world applications, remains an intricate and under-explored problem. To address this, we ...
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 ...
The early diagnosis and accurate classification of lung cancer have a critical impact on clinical treatment and patient survival. The rise of artificial intelligence technology has led to ...
In recent years, underwater object detection (UOD) has become a prominent research area in the computer vision community. However, existing UOD approaches are still vulnerable to underwater ...
Abstract: The objective of hyperspectral remote sensing image salient object detection (HRSI-SOD) is to identify objects or regions that exhibit distinct spectrum contrasts with the background. This ...
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 ...
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