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pro vyhledávání: '"Jones Kate"'
Autor:
Vendrow, Edward, Pantazis, Omiros, Shepard, Alexander, Brostow, Gabriel, Jones, Kate E., Mac Aodha, Oisin, Beery, Sara, Van Horn, Grant
We introduce INQUIRE, a text-to-image retrieval benchmark designed to challenge multimodal vision-language models on expert-level queries. INQUIRE includes iNaturalist 2024 (iNat24), a new dataset of five million natural world images, along with 250
Externí odkaz:
http://arxiv.org/abs/2411.02537
Autor:
Pantazis, Omiros, Bevan, Peggy, Pringle, Holly, Ferreira, Guilherme Braga, Ingram, Daniel J., Madsen, Emily, Thomas, Liam, Thanet, Dol Raj, Silwal, Thakur, Rayamajhi, Santosh, Brostow, Gabriel, Mac Aodha, Oisin, Jones, Kate E.
Large wildlife image collections from camera traps are crucial for biodiversity monitoring, offering insights into species richness, occupancy, and activity patterns. However, manual processing of these data is time-consuming, hindering analytical pr
Externí odkaz:
http://arxiv.org/abs/2408.14348
Autor:
Williams, Ben, van Merriënboer, Bart, Dumoulin, Vincent, Hamer, Jenny, Triantafillou, Eleni, Fleishman, Abram B., McKown, Matthew, Munger, Jill E., Rice, Aaron N., Lillis, Ashlee, White, Clemency E., Hobbs, Catherine A. D., Razak, Tries B., Jones, Kate E., Denton, Tom
Machine learning has the potential to revolutionize passive acoustic monitoring (PAM) for ecological assessments. However, high annotation and compute costs limit the field's efficacy. Generalizable pretrained networks can overcome these costs, but h
Externí odkaz:
http://arxiv.org/abs/2404.16436