Abstract: Object detection in event streams has emerged as a cutting-edge research area, demonstrating superior performance in low-light conditions, scenarios with motion blur, and rapid movements.

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 ...

Spiking Neural Networks (SNNs), inspired by neuroscience principles, have gained attention for their energy efficiency. However, directly trained SNNs lag behind Artificial Neural Networks (ANNs) in ...

Abstract: Object detection is the method of recognizing and finding objects in digital images and video frames. Over the years, object detection techniques have made significant advances driven 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 ...

Spending hours manually creating address objects on your Palo Alto Networks firewall? There’s a smarter, faster way! This guide will show you how to leverage the Pan-OS REST API and Python to automate ...

A Python library to evaluate mean Average Precision(mAP) for object detection. Provides the same output as PASCAL VOC's matlab code. You can now build a custom Mask RCNN model using Tensorflow Object ...