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Epic-Sounds: A Large-scale Dataset of Actions That Sound

Autor: Huh, J, Chalk, J, Kazakos, E, Damen, D, Zisserman, A

We introduce EPIC-SOUNDS, a large-scale dataset of audio annotations capturing temporal extents and class labels within the audio stream of the egocentric videos. We propose an annotation pipeline where annotators temporally label distinguishable aud

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d88ad57198c5a410dc78ef8863fee8d

With a Little Help from my Temporal Context: Multimodal Egocentric Action Recognition

Autor: Kazakos, E, Huh, J, Nagrini, A, Zisserman, A, Damen, D

Publikováno v: Kazakos, V, Huh, J, Nagrani, A, Zisserman, A & Damen, D 2021, ' With a Little Help from my Temporal Context: Multimodal Egocentric Action Recognition ', Paper presented at The 32nd British Machine Vision Conference, 22/11/21-25/11/21 . < https://www.bmvc2021.com/ >

In egocentric videos, actions occur in quick succession. We capitalise on the action's temporal context and propose a method that learns to attend to surrounding actions in order to improve recognition performance. To incorporate the temporal context

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c5cf8ea96b115920cf76f238da9ea15
http://arxiv.org/abs/2111.01024

Engineering living and regenerative fungal-bacterial biocomposite structures

Autor: Ross M. McBee, Christian Munck, Christopher A. Voigt, Andrew Kaufman, Tarun Srinivasan, Nikita Mukhitov, Haorong Chen, Damen D. Schaak, Miles Richardson, Max Reitman, De-Chuan Meng, Matt Lucht, Harris H. Wang

Publikováno v: Nature materials. 21(4)

Engineered living materials could have the capacity to self-repair and self-replicate, sense local and distant disturbances in their environment, and respond with functionalities for reporting, actuation or remediation. However, few engineered living

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::778a3fc85cbcccf3f2ad16ed953a44d6
https://pubmed.ncbi.nlm.nih.gov/34857911

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