Abstract: Object detection refers to the identification of objects where the presence, location, and size are determined while putting on the corresponding class labels. Object detection is sensitive ...

Abstract: Remote sensing object detection faces challenges such as small object sizes, complex backgrounds, and computational constraints. To overcome these challenges, we propose XSNet, an efficient ...

amlmodelmonitoring/ ├── .env # Environment variables (create from template) ├── set_env.ps1 # Loads .env variables into PowerShell session ├── requirements.txt # Python dependencies │ ├── ...

AWS Lambda provides a simple, scalable, and cost-effective solution for deploying AI models that eliminates the need for expensive licensing and tools. In the rapidly evolving landscape of artificial ...

The XGBoost-based approach demonstrated robust external validation across multiple centers, supporting clinical adoption to guide personalized treatment decisions. A machine learning (ML) model using ...

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 ...

A simple Flask application that can serve predictions machine learning model. Reads a pickled sklearn model into memory when the Flask app is started and returns predictions through the /predict ...

This fact sheet describes TEC, an SEI-developed tool that helps teams avoid mismatches during the development, deployment, and sustainment of ML-enabled systems. Organizations that develop ...