Noncooperative target detection in real-world scenarios relies on large-scale deep neural networks after image capture. However, directly implementing this detection pipeline under conventional ...

Target detection is a critical task in interpreting aerial images. Small target detection, such as vehicles, is challenging. Different lighting conditions affect the accuracy of vehicle detection. For ...

A smart vehicle access control system using machine learning and Supabase. The ML component processes video streams to detect and identify vehicles in real-time. The UI enables users to register ...

Improve this page Add a description, image, and links to the vehicle-collision-detection topic page so that developers can more easily learn about it. Curate this topic ...

The flowchart presented in Figure 1 outlines the proposed method for vehicle detection and re-identification (Re-ID), organized into three main phases: data acquisition, vehicle detection and ...

Our image processing pipeline is meticulously designed to ensure accurate and efficient feature extraction, a critical step in identifying severe accidents. Leveraging deep learning models like ResNet ...

After segmenting the image using Fuzzy C-Means (FCM) and Contour based segmentation (CBS) to reduce image complexity, EfficientDet is used for vehicle detection.