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Deep learning for plant identification using vein morphological patterns
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DOI：10.1016/j.compag.2016.07.003.png)
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摘要
En 中文
We propose using a deep convolutional neural network (CNN) for the problem of plant identification from leaf vein patterns. In particular, we consider classifying three different legume species: white bean, red bean and soybean. The introduction of a CNN avoids the use of handcrafted feature extractors as it is standard in state of the art pipeline. Furthermore, this deep learning approach significantly improves the accuracy of the referred pipeline. We also show that the reported accuracy is reached by increasing the model depth. Finally, by analyzing the resulting models with a simple visualization technique, we are able to unveil relevant vein patterns. (C) 2016 Elsevier B.V. All rights reserved.
Keyword:
Deep learning
Machine vision
Automatic plant identification
Leaf vein image
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期刊
IF:
8.9
论文数:
1.0W
被引数:
4.8W
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引用论文
Decline of Leaf Hydraulic Conductance with Dehydration: Relationship to Leaf Size and Venation Architecture.png)
PLANT PHYSIOLOGYOAAI
PLANT PHYSIOLOGYIF6.9
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