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 ...

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 ...

Abstract: Underwater object detection using SONAR images is critical for marine conservation, environmental monitoring, waste management, and rescue operations. In this study, the authors apply ...

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 ...

What if you could teach a computer to recognize a zebra without ever showing it one? Imagine a world where object detection isn’t bound by the limits of endless training data or high-powered hardware.

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 ...

Tired of manually creating address objects one by one in your Palo Alto Networks firewall? There’s a better way! This comprehensive guide will show you how to leverage the power of the Pan-OS Python ...

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.