Oriented object detection in remote sensing imagery has emerged as a critical field of study, addressing the challenge of recognising and localising objects that appear at arbitrary angles in aerial ...

Abstract: This paper presents an enhanced approach to real-time object detection, addressing challenges such as movement dynamics and environmental variability. The proposed method employs transfer ...

Earnings announcements are one of the few scheduled events that consistently move markets. Prices react not just to the reported numbers, but to how those numbers compare with expectations. A small ...

Existing Incremental Object Detection (IOD) methods partially alleviate catastrophic forgetting when incrementally detecting new objects in real-world scenarios. However, many of these methods rely on ...

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 ...

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 ...

I am working on an overhead object detection project using images with a resolution of 1280x1024. The objects are generally small (e.g., cars and people). The inference will be performed on the DPU.