VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation

VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation

Applying deep learning to images of cropping systems provides new knowledge and insights in research and commercial applications. Semantic segmentation or pixel-wise classification, of RGB images acquired at the ground level, into vegetation and background is a critical step in the estimation of sev...

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Bibliographic Details
Main Authors: Baret, F. (Author), Camacho, F. (Author), Chapman, S.C (Author), Daubige, G. (Author), David, E. (Author), De Solan, B. (Author), Guo, W. (Author), Irfan, K. (Author), James, C. (Author), Madec, S. (Author), Samatan, L.B (Author), Serouart, M. (Author), Smith, D. (Author), Velumani, K. (Author), Weiss, M. (Author)
Format: Article
Language:English
Published: NLM (Medline) 2023
Subjects:
article
benchmarking
canopy
convolutional neural network
crop
cropping system
deep learning
illumination
indoor environment
nonhuman
segmentation algorithm
vegetation
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