A deep learning framework for multi-animal pose tracking.
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Updated
May 20, 2024 - Python
A deep learning framework for multi-animal pose tracking.
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
A list of Human-Object Interaction Learning.
Collection of scripts that utilize Twitter API for suspicious behavior analysis
Leverages biometric and behavioristic data to gain comprehensive insights into user experience, with a focus on improving UX design through data-driven understanding.
Variational Animal Motion Embedding - A tool for time series embedding and clustering
A selection of state-of-the-art research materials on trajectory prediction
This project employs XGBoost regression and XGBoost classifier model to predict user order and user churn on online travel agency data. Reach 97% prediction accuracy.
Behavioral Observation Research Interactive Software
The SCARF-UI is an extension of the SCARF review tool for appraising results from single-case experimental designs (SCEDs)
1000-People-Passenger-Behavior-Recognition-Data
Code for running CFD simulation of larval zebrafish, and MATLAB code for pre/postprocessing. Accompanies the preprint "Behavioral adaptation to changing energy constraints via altered frequency of movement selection" by T. Darveniza, S.I. Zhu, Z. Pujic, B. Sun, M. Levendosky, R. Wong, R. Agarwal, M. H. McCullough, G. J. Goodhill (2023)
🧠Behavior Change as a Service🌞
I created this notebook to help me with behavioral neuroscience experiments. It calculates the average positions and velocities of two body parts (for better accuracy), and creates visualizations such as GIFs and streamline plots to represent the motion and flow of movement.
Customer Product Purchase Behavior Analysis
live, low-latency markerless multi-camera 3D animal tracking system
JS Library for user behaviour tracking from the browser, using mouse movements, clicks, scroll, and time on page.
A teaching machine for free behavioral experiments
Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.
Python Package for the ETBD
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