IEEE

Anomaly Detection in GeoLLM Using Variational Autoencoder

Abstract: Geospatial-based Large Language Models are an emerging technology based on the geospatial locations and the different applications based on the locations. From the survey, it is seen that ...
IEEE

Deep Learning for Anomaly Detection: A CNN-LSTM Autoencoder Approach

Abstract: Due to the significant growth of video surveillance installations in recent years, video anomaly detection has attracted considerable interest in the security sector. Detecting anomalies in ...
GitHub

Global Interpretable Graph-level Anomaly Detection Via Prototype

This is the code for GLADPro - KDD-2025. Thanks to the PyG library. The paper is now available at ACM. If you use our code or results, please kindly cite our paper. @inproceedings{yang2025global, ...
WBAL-TV

Omnilert AI gun detection alerts at Baltimore County schools only get reviewed for major events

HEADQUARTERS IN TOWSON. STOP WALKING. GET ON YOUR KNEES. AN AI GUN DETECTION SYSTEM SENT BALTIMORE COUNTY POLICE TO TWO HIGH SCHOOLS IN THE PAST FEW WEEKS FOR A REPORT ON A WEAPON ON CAMPUS. BOTH TURN ...
GitHub

Time Series Analysis with LSTM, ARIMA, Prophet, and Anomaly Detection

├── src/ # Source code modules │ ├── lstm_model.py # LSTM implementation with PyTorch │ ├── forecasting_models.py # ARIMA, Prophet, and statistical models │ ├── anomaly_detection.py # Anomaly ...