OutcropHyBNet: Hybrid Backbone Networks with Data Augmentation for Accurate Stratum Semantic Segmentation of Monocular Outcrop Images in Carbon Capture and Storage Applications.

Madokoro, Hirokazu; Sato, Kodai; Nix, Stephanie; Chiyonobu, Shun; Nagayoshi, Takeshi; Sato, Kazuhito

Madokoro, Hirokazu; Sato, Kodai; Nix, Stephanie; Chiyonobu, Shun; Nagayoshi, Takeshi; Sato, Kazuhito.

Afiliación

Madokoro H; Faculty of Software and Information Science, Iwate Prefectural University, Takizawa 020-0693, Japan.
Sato K; Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo 015-0055, Japan.
Nix S; Faculty of Software and Information Science, Iwate Prefectural University, Takizawa 020-0693, Japan.
Chiyonobu S; Graduate School of International Resource Sciences, Akita University, Akita 010-8502, Japan.
Nagayoshi T; Faculty of Bioresource Sciences, Akita Prefectural University, Akita 010-0195, Japan.
Sato K; Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo 015-0055, Japan.

Sensors (Basel) ; 23(21)2023 Oct 29.

Article en En | MEDLINE | ID: mdl-37960509

Palabras clave

Convolutional Neural Network; Generative Adversarial Networks; Vision Transformer; drone; outcrop images; semantic segmentation

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Japón

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