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 ...

S3OD is a large-scale fully synthetic dataset for salient object detection and background removal, with 140K high-quality images generated using diffusion models. Our model, trained on large-scale ...

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 ...

We propose a synthetic data generation and annotation framework that enables panoramic object detection using existing large-scale planar image datasets. Instead of relying solely on limited ...

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 ...

Introduction: Recent advances in artificial intelligence have transformed the way we analyze complex environmental data. However, high-dimensionality, spatiotemporal variability, and heterogeneous ...