An ETL tool for transforming four well-known Event-Detection datasets into a unified common schema.

10000-Chinese-News-Events-Annotation-Data

Windows text-to-speech critical event ID detector.

Python implementation of WhatsUp for co-occurring event resolution in social media data

A Single-Station Earthquake Detection and Phase-Picking Network Based on a Multiple Attention Mechanism

10496-Images-Data-Of-Outdoor-BBQ

This code detects events from news articles using BINets (this was programmed following the Microsoft paper of the same name)

The task of event extraction and news clustering is done in this repository using simple clustering algorithms and news-api.

Social Media Event Detection

Audio-based Multimedia Event Detection

Check out the source code for the QT9 QMS File Sorter program. This tool automatically detects newly created files in specified folders, moves them to matching folders based on predefined names, and appends the creation date to each file name for organized storage.

A serverless API that detects and summarizes global events — such as disasters, armed conflicts, and emergencies — using scraped data from Google News and Twitter (X). Built on Vercel’s serverless infrastructure for effortless deployment and performance at scale.

Content annotation bank for Bangla. It includes, named entity, temporal expressions, relation, and event annotation.

Detecting potential corruption events from public expenditure time-series data

AutoEncoders for Event Detection (AEED): a Keras-based class for anomaly detection in water sensor networks.

Simple recording app that saves recordings as matrices containing time-frequency data

Repository for QA-based event detection and extraction from news and social media.

a “message intelligence platform” that reads billions of messages to answer four questions: “who you are, what you do, how do you think, and what is your relationship with others.”

Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs (WWW 2021)

Implementation and comparison of Gaze Shifts identification methods for Moving Observers in Dynamic Environments