Abstract: This study develops a scalable, effective, and user-friendly solution to tackle the problem of real-time object detection in photos. The suggested approach ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

This project showcases a sophisticated pipeline for object detection and segmentation using a Vision-Language Model (VLM) and the Segment Anything Model 2 (SAM2). The core idea is to leverage the ...

Abstract: The capability of automated object detection has received considerable focus over the last few years within the domains of self-driving cars as well as military-grade surveillance systems, ...

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 ...

Comcast's Xfinity has introduced a new feature in its internet routers called Wi-Fi Motion, which uses Wi-Fi signals to detect movement in your home, whether from people, pets or other moving objects.

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...

Below are examples of differences between the inference results of the AI model and the detection and counting results of expert analysts. Figure 2 shows the fiber detection results for image B-4. In ...

Small object detection is a critical task in applications like autonomous driving and ship black smoke detection. While Deformable DETR has advanced small object detection, it faces limitations due to ...