Leaf App: Leaf recognition with deep convolutional neural networks

被引：0

作者：

Sugata, T. L. I. ^{[1
]}

Yang, C. K. ^{[1
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Dept Informat Management, Taipei 106, Taiwan

来源：

INTERNATIONAL CONFERENCE ON INFORMATICS, TECHNOLOGY AND ENGINEERING 2017 (INCITE 2017) | 2017年 / 273卷

关键词：

D O I：

10.1088/1757-899X/273/1/012004

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, a very deep convolutional neural network is used to do leaf recognition. In order to predict location of leaves, some pre-processing technique is adopted to extract regions in the image before doing classification. To improve the accuracy, we enlarge the dataset by data augmentation, i.e., doing several transformations such as horizontal reflection, contrast enhancement and rotations. Experimental results show that by using deep convolutional neural network with data augmentation, our system can achieve accuracy close to the state-of-the-art systems.

引用

页数：6

共 50 条

[31] Deep Convolutional Network for Citrus Leaf Diseases Recognition [J].

Chen, Quan ;

Liu, Xin ;

Dong, Caixia ;

Tong, Tong ;

Yang, Changcai ;

Chen, Riqing ;

Zou, Tengyue ;

Yang, Xiaolang .

2019 IEEE INTL CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, BIG DATA & CLOUD COMPUTING, SUSTAINABLE COMPUTING & COMMUNICATIONS, SOCIAL COMPUTING & NETWORKING (ISPA/BDCLOUD/SOCIALCOM/SUSTAINCOM 2019), 2019, :1490-1494

[32] Deep convolutional neural network based plant species recognition through features of leaf [J].

Dhananjay Bisen .

Multimedia Tools and Applications, 2021, 80 :6443-6456

[33] Deep convolutional neural network based plant species recognition through features of leaf [J].

Bisen, Dhananjay .

MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (04) :6443-6456

[34] Palm-Leaf Manuscript Character Recognition and Classification Using Convolutional Neural Networks [J].

Sabeenian, R. S. ;

Paramasivam, M. E. ;

Anand, R. ;

Dinesh, P. M. .

COMPUTING AND NETWORK SUSTAINABILITY, 2019, 75

[35] Rubber Leaf Disease Recognition Based on Improved Deep Convolutional Neural Networks With a Cross-Scale Attention Mechanism [J].

Zeng, Tiwei ;

Li, Chengming ;

Zhang, Bin ;

Wang, Rongrong ;

Fu, Wei ;

Wang, Juan ;

Zhang, Xirui .

FRONTIERS IN PLANT SCIENCE, 2022, 13

[36] WikiFish: Mobile App for Fish Species Recognition Using Deep Convolutional Neural Networks [J].

Kholoud, K. K. B. Elbatsh ;

Ibrahim, I. Y. S. Sokar ;

Shareef, S. T. R. Rajab .

2021 THE 4TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INTELLIGENT SYSTEMS, CIIS 2021, 2021, :13-18

[37] Deep Convolutional Neural Networks for South Indian Mango Leaf Disease Detection and Classification [J].

Thaseentaj, Shaik ;

Ilango, S. Sudhakar .

CMC-COMPUTERS MATERIALS & CONTINUA, 2023, 77 (03) :3593-3618

[38] Detecting tomato leaf diseases by image processing through deep convolutional neural networks [J].

Hossain, Md. Iqbal ;

Jahan, Sohely ;

Asif, Md. Rashid Al ;

Samsuddoha, Md. ;

Ahmed, Kawsar .

SMART AGRICULTURAL TECHNOLOGY, 2023, 5

[39] Identification of Apple Leaf Diseases by Improved Deep Convolutional Neural Networks With an Attention Mechanism [J].

Wang, Peng ;

Niu, Tong ;

Mao, Yanru ;

Zhang, Zhao ;

Liu, Bin ;

He, Dongjian .

FRONTIERS IN PLANT SCIENCE, 2021, 12

[40] Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification [J].

Sladojevic, Srdjan ;

Arsenovic, Marko ;

Anderla, Andras ;

Culibrk, Dubravko ;

Stefanovic, Darko .

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2016, 2016

← 1 2 3 4 5 →