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Generalization vs Specialization in Computer Vision for Ecology

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If you have a question about this talk, please contact Annabelle Scott .

There are explicit tradeoffs between generality and specificity in computer vision methods with respect to designing impactful end-to-end solutions for ecological challenges — computer vision systems that are general purpose but optimal for each stakeholder, taking into account cost, human effort, and risk. We explore these tradeoffs across several dimensions, investigating the impact of generality vs specificity with regards to data, labels, tasks, and models, and propose joint compression and specialization of large generalist models as an efficient and cost-effective alternative to retraining or fine tuning in resource-constrained scenarios such as remote field-based ecological monitoring.

This talk is part of the AI4ER Seminar Series series.

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Webinar & LT2, Computer Laboratory, William Gates Building. Seminar Room, PPSIS, New Museums Site https://zoom.us/j/93027658238

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