@inproceedings{4e99007753fd4dbbb3bf019cd40ee13a,
title = "Leaf recognition for plant classification based on wavelet entropy and back propagation neural network",
abstract = "In this paper, we proposed a method for plant classification, which aims to recognize the type of leaves from a set of image instances captured from same viewpoints. Firstly, for feature extraction, this paper adopted the 2-level wavelet transform and obtained in total 7 features. Secondly, the leaves were automatically recognized and classified by Back-Propagation neural network (BPNN). Meanwhile, we employed K-fold cross-validation to test the correctness of the algorithm. The accuracy of our method achieves 90.0%. Further, by comparing with other methods, our method arrives at the highest accuracy.",
keywords = "Back-Propagation, Classification, Feature extraction, K-fold cross-validation, Pattern recognition",
author = "Yang, {Meng Meng} and Preetha Phillips and Shuihua Wang and Yudong Zhang",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017 ; Conference date: 16-08-2017 Through 18-08-2017",
year = "2017",
doi = "10.1007/978-3-319-65298-6_34",
language = "English",
isbn = "9783319652979",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "367--376",
editor = "Honghai Liu and YongAn Huang and Hao Wu and Zhouping Yin",
booktitle = "Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings",
}