20230505 Webinar: Using BisQueAI's Image Analysis Capabilities for Wildlife Conservation

BisQue is an open-source data storage and analysis web service developed by the Vision Research Lab (VRL) at UC Santa Barbara that offers a powerful platform for analyzing 4-dimensional image data. BisQue’s array of tools for image processing, analysis, and visualization makes it a versatile solution for a wide range of applications. Additionally, BisQue's unique architecture allows users to run any containerized AI module, making it a highly customizable and adaptable platform for data analysis.
This webinar highlights a new collaborative project involving BisQue’s creators and researchers at the Smithsonian National Zoo and Conservative Biology Institute. Recognizing that BisQue is an ideal application for wildlife monitoring and conservation, Smithsonian researchers sought to deploy the BisQue services to help analyze aerial wildlife survey data in grasslands of North America and East Africa. The BisQue-Smithsonian collaboration is focused on developing cutting edge AI/Deep Learning solutions for quantitative aerial image/video analysis, in order to detect, track and monitor wildlife in remote areas. Researchers are using BisQue to manage large volumes of imaging data, annotate these data to train state-of-the-art AI models, and then use these models to automatically detect and locate animals to better understand the factors necessary for conservation of critical wildlife populations. Presenters include Lacey Hughey of The Smithsonian Institution; Connor Levenson and Satish Kumar of Dr. BS Manjunath's UCSB-VRL/Center for Multimodal Big Data Science. Join us to learn how AI-powered and computational scientific research technology is being harnessed for a more resilient and biodiverse planet.