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Computer Vision for Global-Scale Biodiversity Monitoring

Offered By: Paul G. Allen School via YouTube

Tags

Computer Vision Courses Artificial Intelligence Courses Climate Change Courses Sustainability Courses Biodiversity Courses Conservation Courses Data Processing Courses

Course Description

Overview

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Explore a compelling lecture on the development of real-time, modular earth observation systems for global-scale impact in sustainability and conservation. Delve into the challenges of ecological monitoring in the face of climate change and learn about innovative approaches to overcome them. Discover how interdisciplinary collaboration and automated data processing can revolutionize conservation efforts. Gain insights into cutting-edge computer vision methods for efficient, accessible, and equitable global-scale biodiversity monitoring. Understand the importance of addressing spatiotemporal correlations, imperfect data quality, and long-tailed distributions in ecological data. Learn about the speaker's research agenda, which aims to incorporate multiple data modalities, expert knowledge, and ethical considerations into AI systems for conservation. Hear from Sara Beery, a PhD Candidate at Caltech, about her work in breaking down knowledge barriers between fields and her efforts to increase diversity and inclusion in STEM.

Syllabus

Allen School Colloquium: Sara Beery (CalTech)


Taught by

Paul G. Allen School

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