AN INCREMENTAL LEARNING METHOD FOR CLASSIFICATION OF PLANT LEAVES USING DEEP LEARNING

被引:0
作者
Prasad, P. Siva [1 ]
Senthilrajan, A. [2 ]
机构
[1] Alagappa Univ, Dept Comp Sci, Karikudi 630003, Tamil Nadu, India
[2] Alagappa Univ, Dept Computat Logist, Karikudi 630003, Tamil Nadu, India
来源
ADVANCES AND APPLICATIONS IN MATHEMATICAL SCIENCES | 2021年 / 20卷 / 11期
关键词
Leaf; Machine Learning; Deep Learning; CNN; Boost incremental learning;
D O I
暂无
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Research on plant leaves is an impact on Agriculture. Plant leaves have an essential role in environmental protection. Recognition of plant leaves is essential to agricultural environments. A leaf dataset has a collection of shape and vein, colour, and texture features extracted from digital leaf images. In this paper, we have used Flavia dataset and we have proposed a Boost incremental learning method to train the model on small leaf sub-datasets when extracted features are huge to place into memory. Due to this boost incremental approach, we have obtained 98% accuracy in classification of plant leaves. This work addresses and provides better solutions for classification of plant leaves using Convolutional Neural Network.
引用
收藏
页码:2607 / 2611
页数:5
相关论文
共 6 条
[1]   Deep Residual Learning for Image Recognition [J].
He, Kaiming ;
Zhang, Xiangyu ;
Ren, Shaoqing ;
Sun, Jian .
2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2016, :770-778
[2]  
Howard A.G., 2017, ARXIV, V1704, P4861
[3]   Densely Connected Convolutional Networks [J].
Huang, Gao ;
Liu, Zhuang ;
van der Maaten, Laurens ;
Weinberger, Kilian Q. .
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017), 2017, :2261-2269
[4]  
REBUFFI SA, 2016, C COMP VIS PATT REC
[5]   Incremental Learning of Object Detectors without Catastrophic Forgetting [J].
Shmelkov, Konstantin ;
Schmid, Cordelia ;
Alahari, Karteek .
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2017, :3420-3429
[6]   Error-Driven Incremental Learning in Deep Convolutional Neural Network for Large-Scale Image Classification [J].
Xiao, Tianjun ;
Zhang, Jiaxing ;
Yang, Kuiyuan ;
Peng, Yuxin ;
Zhang, Zheng .
PROCEEDINGS OF THE 2014 ACM CONFERENCE ON MULTIMEDIA (MM'14), 2014, :177-186