Deep video anomaly detection in automated laboratory setting

Ali Dabouei, Jishnu Parayil Shibu, Vibhu Dalal, Chengzhi Cao, Andy Macwilliams, Joshua Kangas, Min Xu

Abstract: Highlights•Introduced a deep video anomaly detection framework in automated laboratory setting.•The model estimates the score for the video and individual pipettes.•The model exhibits notable performance when tested against the evaluation samples.