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Skildring:Figure 2 from Ordoñez, Alba, Ingrid Utseth, Olav Brautaset, Rolf Korneliussen, and Nils Olav Handegard. “Evaluation of Echosounder Data Preparation Strategies for Modern Machine Learning Models.” Fisheries Research 254 (October 1, 2022): 106411. https://doi.org/10.1016/j.fishres.2022.106411.
Kode: HAV-67229
Kreditering: Alba Ordoñes / Havforskningsinstituttet
Søkeord: CRIMAC, Deep learning, Machine learning, xxxInExternalxxx
AI-søkeord: batchnormalisering, konvolusjonslag, djuplearning-diagram, enkoder-dekoder-struktur, funksjonskart, bildesegmentering, maks-pooling, nevralt nettverksarkitektur, ReLU-aktivering, U-Net-modell
AI-tekster: (b), (a), 2562, A, concatenated feature maps, softmax, conv 1x1, 2562, 4 64 64, 2562, 2562, 4+1 64 64, 2562, 2562, 32, 2562, 2562, 162, 512 1024 1024, 162, 512 1024 1024, -- Other layers presented, in Brautaset et al., 2020, copy, transposed conv 2x2, max pool 2x2, 2562, 32, 2562, 128 64 64, 2562, 2562, 128 64 64 3 3, 2562, 2562, 2562, 2562, 2562, 64+1 3, 2562, 2562, 2562, 2562, 3, (b), (a), 2562, A, concatenated, feature, maps, softmax, conv, 1x1, conv, batch, norm,, ReLU, 2562, 4, 64, 64, 2562, 2562, 4+1, 64, 64, 2562, 2562, 32, 2562, 2562, 162, 512, 1024, 1024, 162, 512, 1024, 1024, Other, layers, presented, in, Brautaset, et, al.,, 2020, copy, transposed, conv, 2x2, max, pool, 2x2, 2562, 32, 2562, 128, 64, 64, 2562, 2562, 128, 64, 64, 3, 3, 2562, 2562, 2562, 2562, 2562, 64+1, 3, 2562, 2562, 2562, 2562, 3
Alternativ tekst: Diagram som samanliknar to nevrale nettverksarkitekturar (a) og (b) som viser U-Net-stil enkoder-dekodar med konvolusjonslag.
Filtypar: Original (1663 x 1885), Liten(JPG) (953 x 1080)

HAV-67229
Figure 2 from Ordoñez, Alba, Ingrid Utseth, Olav Brautaset, Rolf Korneliussen, and Nils Olav Handegard. “Evaluation of Echosounder Data Preparation Strategies for Modern Machine Learning Models.” Fisheries Research 254 (October 1, 2022): 106411. https://doi.org/10.1016/j.fishres.2022.106411.
Alba Ordoñes / Havforskningsinstituttet
Original (1663 x 1885)
Liten(JPG) (953 x 1080)

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