The adversarial sample detection model based on edge noise feature
-
Updated
Nov 24, 2021 - HTML
The adversarial sample detection model based on edge noise feature
Live time object detector. Contributions are welcomed for more diversified models
🔔 숙명여자대학교 인공지능공학부 CODE - IT 학회 2024 여름방학 프로젝트 | 2024 Summer Project of CODE - IT Association @ Sookmyung Women's University
Deteccion de cascos de seguridad en un sitio web utilizando el modelo YOLO e imagenes de Roboflow para reentrenar
IoT-based smart manhole detection system using object detection.
A robust machine learning framework to detect spear-phishing emails using NLP, XGBoost, and TensorFlow. Includes explainability (SHAP/LIME), real-time prediction (FastAPI), monitoring (Prometheus + Grafana), and async feedback handling (Redis). Designed for scalability, transparency, and production-readiness.
Add a description, image, and links to the detection-model topic page so that developers can more easily learn about it.
To associate your repository with the detection-model topic, visit your repo's landing page and select "manage topics."