Data for: Branch Detection for Apple Trees Trained in Fruiting Wall Architecture using Depth Features and Regions-Convolutional Neural Network (R-CNN)

Name: Data for: Branch Detection for Apple Trees Trained in Fruiting Wall Architecture using Depth Features and Regions-Convolutional Neural Network (R-CNN)
Creator: Jing Zhang
Published: 2018-11-14T22:28:13.868Z
Keywords: Agricultural Engineering, Machine Vision, Deep Learning

Zhang, Jing; He, Long; Gao, Zongmei; Zhang, Xin; Zhang, Qin; Karkee, Manoj

doi:10.17632/kvpmv75hvg.8

Data for: Branch Detection for Apple Trees Trained in Fruiting Wall Architecture using Depth Features and Regions-Convolutional Neural Network (R-CNN)

Published: 14 November 2018| Version 8 | DOI: 10.17632/kvpmv75hvg.8

Contributors:

Jing Zhang,

Long He,

Zongmei Gao,

Xin Zhang,

Qin Zhang,

Manoj Karkee

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This data mainly includes the testing images of apple tree branches in our paper, and the corresponding R-CNN detection results.

Data for: Branch Detection for Apple Trees Trained in Fruiting Wall Architecture using Depth Features and Regions-Convolutional Neural Network (R-CNN)

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