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Alexander Hsu, Ph.D.'s Projects

b-soid icon b-soid

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.

behavetrack icon behavetrack

BehaveTrack uses user-specific B-SOiD classifier to predict behavior based on pose. Generate ethogram and summary statistics for animal recordings. Intuitive interface for tagging and grouping files. Enhance animal behavior studies with accurate and reliable predictions.

data-org icon data-org

Yttri-Lab data structure on 16TB hard-drive

dlc_protocol icon dlc_protocol

Instructions for using deeplabcut v2.1.7 on a cluster (specifically Bridges GPU-AI node at PSC)

lupe-bsoid-cloud icon lupe-bsoid-cloud

LUPE X B-SOiD is a no code website for behavior analysis that allows users to predict and analyze behavior using 2D pose estimation. Its customized naming system fits experimental contexts, while detailed analysis and reactive visualization design help identify trends. Downloadable CSV files make integration with existing workflows easy.

sleap icon sleap

A deep learning framework for multi-animal pose tracking.

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