Development of Impurity-Detection System for Tracked Rice Combine Harvester Based on DEM and Mask R-CNN.

Guan, Zhuohuai; Li, Haitong; Chen, Xu; Mu, Senlin; Jiang, Tao; Zhang, Min; Wu, Chongyou

Guan, Zhuohuai; Li, Haitong; Chen, Xu; Mu, Senlin; Jiang, Tao; Zhang, Min; Wu, Chongyou.

Afiliação

Guan Z; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China.
Li H; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China.
Chen X; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China.
Mu S; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China.
Jiang T; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China.
Zhang M; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China.
Wu C; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China.

Sensors (Basel) ; 22(23)2022 Dec 06.

Article em En | MEDLINE | ID: mdl-36502249

Assuntos

Oryza; Grão Comestível; Reconhecimento Psicológico; Algoritmos; Calibragem

Palavras-chave

Mask R-CNN; combine harvester; discrete element method; impurity rate; rice

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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