A python package for processing eye movement data

Intelligent event detection system using semantic embeddings, MinHash LSH deduplication, and HDBSCAN clustering to transform real-time news streams into coherent timelines

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

PMU data monitoring tool for real-time detection of oscillations in power systems.

A python library for social event detection

Applying Deep Learning Approaches to Volleyball Data

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

Clustering Schemes for Image Analysis

A standardized, fair, and reproducible benchmark for evaluating event extraction approaches

Game events detection using traditional CV techniques

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 comprehensive, unified and modular event extraction toolkit.

The source code for the real-time hand gesture recognition algorithm based on Temporal Muscle Activation maps of multi-channel surface electromyography (sEMG) signals (ICASSP 2021)

Template correlation-based detection of postsynaptic currents.

Segmentation based event detection from Tweets. Published at NAACL SRW 2019

Evaluating ChatGPT’s Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)

A version of the YOLOv3 network capable of handling 1D data inputs.

An Evaluation of ChatGPT on Information Extraction task, including Named Entity Recognition (NER), Relation Extraction (RE), Event Extraction (EE) and Aspect-based Sentiment Analysis (ABSA).

VitalWatch is a cutting-edge ICU Surveillance Event Detection System designed to elevate patient monitoring within hospital intensive care units. Leveraging YOLO for real-time object detection and a Human-in-the-Loop (HITL) system for continuous improvement, this project ensures accurate, adaptive, and comprehensive surveillance.