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Using channel pruning-based YOLO v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environments
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Using channel pruning-based YOLO v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environments

Wu, Dihua ; Lv, Shuaichao ; Jiang, Mei ; Song, Huaibo

Computers and electronics in agriculture, 2020-11, Vol.178, p.105742, Article 105742 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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2
Generative adversarial networks (GANs) for image augmentation in agriculture: A systematic review
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Generative adversarial networks (GANs) for image augmentation in agriculture: A systematic review

Lu, Yuzhen ; Chen, Dong ; Olaniyi, Ebenezer ; Huang, Yanbo

Computers and electronics in agriculture, 2022-09, Vol.200, p.107208, Article 107208 [Periódico revisado por pares]

Elsevier B.V

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A survey of deep learning techniques for weed detection from images
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A survey of deep learning techniques for weed detection from images

Hasan, A S M Mahmudul ; Sohel, Ferdous ; Diepeveen, Dean ; Laga, Hamid ; Jones, Michael G.K.

Computers and electronics in agriculture, 2021-05, Vol.184, p.106067, Article 106067 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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4
Apple detection during different growth stages in orchards using the improved YOLO-V3 model
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Apple detection during different growth stages in orchards using the improved YOLO-V3 model

Tian, Yunong ; Yang, Guodong ; Wang, Zhe ; Wang, Hao ; Li, En ; Liang, Zize

Computers and electronics in agriculture, 2019-02, Vol.157, p.417-426 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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5
Deep learning for classification and severity estimation of coffee leaf biotic stress
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Artigo
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Deep learning for classification and severity estimation of coffee leaf biotic stress

Esgario, José G.M. ; Krohling, Renato A. ; Ventura, José A.

Computers and electronics in agriculture, 2020-02, Vol.169, p.105162, Article 105162 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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6
A review of computer vision technologies for plant phenotyping
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A review of computer vision technologies for plant phenotyping

Li, Zhenbo ; Guo, Ruohao ; Li, Meng ; Chen, Yaru ; Li, Guangyao

Computers and electronics in agriculture, 2020-09, Vol.176, p.105672, Article 105672 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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7
Deep learning in agriculture: A survey
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Deep learning in agriculture: A survey

Kamilaris, Andreas ; Prenafeta-Boldú, Francesc X.

Computers and electronics in agriculture, 2018-04, Vol.147, p.70-90 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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8
Crop yield prediction using machine learning: A systematic literature review
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Crop yield prediction using machine learning: A systematic literature review

van Klompenburg, Thomas ; Kassahun, Ayalew ; Catal, Cagatay

Computers and electronics in agriculture, 2020-10, Vol.177, p.105709, Article 105709 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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9
Deep learning for plant identification using vein morphological patterns
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Deep learning for plant identification using vein morphological patterns

Grinblat, Guillermo L. ; Uzal, Lucas C. ; Larese, Mónica G. ; Granitto, Pablo M.

Computers and electronics in agriculture, 2016-09, Vol.127, p.418-424 [Periódico revisado por pares]

Elsevier B.V

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10
Using deep transfer learning for image-based plant disease identification
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Using deep transfer learning for image-based plant disease identification

Chen, Junde ; Chen, Jinxiu ; Zhang, Defu ; Sun, Yuandong ; Nanehkaran, Y.A.

Computers and electronics in agriculture, 2020-06, Vol.173, p.105393, Article 105393 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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