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 ...

State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China College of Food Science and Technology, Huazhong Agricultural ...

Abstract: Object detection is essential in applications such as healthcare (e.g. organ detection in CT and ultrasound scans), autonomous driving, and surveillance. However, smaller models like YOLOv8 ...

Tea leaf diseases are significant causes of reduced quality and yield in tea production. In the Yunnan region, where the climate is suitable for tea cultivation, tea leaf diseases are small, scattered ...