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Plant Leaf Recognition Using a Convolution Neural Network
Author(s) -
Wang-Su Jeon,
Sang-Yong Rhee
Publication year - 2017
Publication title -
international journal of fuzzy logic and intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.296
H-Index - 9
eISSN - 2093-744X
pISSN - 1598-2645
DOI - 10.5391/ijfis.2017.17.1.26
Subject(s) - deep learning , artificial intelligence , computer science , field (mathematics) , tree (set theory) , convolutional neural network , artificial neural network , convolution (computer science) , machine learning , pattern recognition (psychology) , mathematics , mathematical analysis , pure mathematics
There are hundreds of kinds of trees in the natural ecosystem, and it can be very difficult to distinguish between them. Botanists and those who study plants however, are able to identify the type of tree at a glance by using the characteristics of the leaf. Machine learning is used to automatically classify leaf types. Studied extensively in 2012, this is a rapidly growing field based on deep learning. Deep learning is itself a self-learning technique used on large amounts of data, and recent developments in hardware and big data have made this technique more practical. We propose a method to classify leaves using the CNN model, which is often used when applying deep learning to image processing.

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