Computerized Classification of Fruits using Convolution Neural Network

被引:3
作者
Yamparala, Rajesh [1 ]
Challa, Ramaiah [2 ]
Kantharao, V [2 ]
Krishna, P. Seetha Rama [2 ]
机构
[1] Vignans NirulaInst Technol & Sci Women, Dept CSE, Guntur, Andhra Pradesh, India
[2] Koneru Lakshmaiah Educ Fdn, Dept CSE, Guntur, Andhra Pradesh, India
来源
2020 7TH IEEE INTERNATIONAL CONFERENCE ON SMART STRUCTURES AND SYSTEMS (ICSSS 2020) | 2020年
关键词
Computerized; CNN (Convolution Neural Network); Segmentation; Classification; Filtering; Detection;
D O I
10.1109/icsss49621.2020.9202305
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Now a days automation in every field becomes common. While coming to the agriculture field, it has become necessity for classification of fruits, leaves, soils, climatic conditions for better yielding of farming. Among these classification of fruits is very essential and challenging task as many fruits looks a like interms of colour, shape, size. It is very much needed for computerised detection of diseases in a fruits where early detection protects from damaging the entire crop. Here classification of fruits has become the first step in detection of fruits diseases. Here Convolution Neural Network(CNN) based classification method is proposed which gives a better classification result of 90% compared to other proposed methodologies till now. Experiments are held with the dataset of 200 images of fruits in which apple fruit images are 50,mango 50,orange 50 and the remaining 50 are grapes.
引用
收藏
页码:411 / 414
页数:4
相关论文
共 15 条
  • [1] [Anonymous], HDB BRAIN THEORY NEU
  • [2] Balaji G. N, 2019, EAI ENDORSED T PERVA, V5, P1
  • [3] Basha C. M. A. K. Z., 2019, INT J INNOVATIVE TEC, V9, P1930
  • [4] Computer Aided Fracture Detection System
    Basha, C. M. A. K. Zeelan
    Padmaja, Maruthi
    Balaji, G. N.
    [J]. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2018, 8 (03) : 526 - 531
  • [5] Basha Cmak Zeelan, 2020, 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC). Proceedings, P991, DOI 10.1109/ICCMC48092.2020.ICCMC-000184
  • [6] Basha C. Z., 2019, EXAMINING FRACTAL IM, P188, DOI [10.4018/978-1-7998-0066-8.ch009, DOI 10.4018/978-1-7998-0066-8.CH009]
  • [7] Hou L, 2016, 2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD), P18, DOI 10.1109/FSKD.2016.7603144
  • [8] Krishna A., 2019, INT J INNOVATIVE TEC, V8, P2800
  • [9] Miriyala P., 2019, INT J INNOVATIVE TEC, V9, P2178
  • [10] Oltean Mihai, 2017, ARXIV PREPRINT ARXIV