Identification and classification of Green Leafy Vegetables using CNN models

Eneia Filipe Vilanculos; Thokozani Shongwe; Ali N. Hasan

doi:10.1109/icABCD59051.2023.10220482

Identification and classification of Green Leafy Vegetables using CNN models

Eneia Filipe Vilanculos
, Thokozani Shongwe
, Ali N. Hasan

Electrical and Electronic Engineering Technology

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

Identifying and classifying vegetables in big farms is a challenge, especially when the vegetables are similar in colour and shape. Manual identification of vegetables takes time and is prone to errors. Therefore, the automatic classification process of the precision farming, increasingly using image processing and pattern recognition to identify fruits and vegetable, is becoming essential to identify and classify vegetables in big farms. In this paper, an automatic system for the identification and classification of green leafy vegetables, similar in colour and shape was evaluataed using five different deep learning models such as CNN, MobileNet, VGG-16, Inception V3 and ResNet 50. The accuracies of these models achieved in this paper vary from 67% to 99%. The model with the highest accuracy is the MobileNet.

Original language	English
Title of host publication	6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings
Editors	Sameerchand Pudaruth, Upasana Singh
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350314809
DOIs	https://doi.org/10.1109/icABCD59051.2023.10220482
Publication status	Published - 2023
Event	6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Durban, South Africa Duration: 3 Aug 2023 → 4 Aug 2023

Publication series

Name	6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings

Conference

Conference	6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023
Country/Territory	South Africa
City	Durban
Period	3/08/23 → 4/08/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger

Keywords

Agriculture
Deep Learning
MobileNet
VGG-16
Vegetables Classification

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Computer Vision and Pattern Recognition
Information Systems
Information Systems and Management

Access to Document

10.1109/icABCD59051.2023.10220482

Cite this

Vilanculos, E. F., Shongwe, T., & Hasan, A. N. (2023). Identification and classification of Green Leafy Vegetables using CNN models. In S. Pudaruth, & U. Singh (Eds.), 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings (6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icABCD59051.2023.10220482

Vilanculos, Eneia Filipe ; Shongwe, Thokozani ; Hasan, Ali N. / Identification and classification of Green Leafy Vegetables using CNN models. 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings. editor / Sameerchand Pudaruth ; Upasana Singh. Institute of Electrical and Electronics Engineers Inc., 2023. (6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings).

@inproceedings{55b6ad169029491fb8151dfd0fed43ff,

title = "Identification and classification of Green Leafy Vegetables using CNN models",

abstract = "Identifying and classifying vegetables in big farms is a challenge, especially when the vegetables are similar in colour and shape. Manual identification of vegetables takes time and is prone to errors. Therefore, the automatic classification process of the precision farming, increasingly using image processing and pattern recognition to identify fruits and vegetable, is becoming essential to identify and classify vegetables in big farms. In this paper, an automatic system for the identification and classification of green leafy vegetables, similar in colour and shape was evaluataed using five different deep learning models such as CNN, MobileNet, VGG-16, Inception V3 and ResNet 50. The accuracies of these models achieved in this paper vary from 67\% to 99\%. The model with the highest accuracy is the MobileNet.",

keywords = "Agriculture, Deep Learning, MobileNet, VGG-16, Vegetables Classification",

author = "Vilanculos, \{Eneia Filipe\} and Thokozani Shongwe and Hasan, \{Ali N.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 ; Conference date: 03-08-2023 Through 04-08-2023",

year = "2023",

doi = "10.1109/icABCD59051.2023.10220482",

language = "English",

series = "6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Sameerchand Pudaruth and Upasana Singh",

booktitle = "6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings",

address = "United States",

}

Vilanculos, EF, Shongwe, T & Hasan, AN 2023, Identification and classification of Green Leafy Vegetables using CNN models. in S Pudaruth & U Singh (eds), 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings. 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023, Durban, South Africa, 3/08/23. https://doi.org/10.1109/icABCD59051.2023.10220482

Identification and classification of Green Leafy Vegetables using CNN models. / Vilanculos, Eneia Filipe; Shongwe, Thokozani; Hasan, Ali N.
6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings. ed. / Sameerchand Pudaruth; Upasana Singh. Institute of Electrical and Electronics Engineers Inc., 2023. (6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Identification and classification of Green Leafy Vegetables using CNN models

AU - Vilanculos, Eneia Filipe

AU - Shongwe, Thokozani

AU - Hasan, Ali N.

PY - 2023

Y1 - 2023

N2 - Identifying and classifying vegetables in big farms is a challenge, especially when the vegetables are similar in colour and shape. Manual identification of vegetables takes time and is prone to errors. Therefore, the automatic classification process of the precision farming, increasingly using image processing and pattern recognition to identify fruits and vegetable, is becoming essential to identify and classify vegetables in big farms. In this paper, an automatic system for the identification and classification of green leafy vegetables, similar in colour and shape was evaluataed using five different deep learning models such as CNN, MobileNet, VGG-16, Inception V3 and ResNet 50. The accuracies of these models achieved in this paper vary from 67% to 99%. The model with the highest accuracy is the MobileNet.

AB - Identifying and classifying vegetables in big farms is a challenge, especially when the vegetables are similar in colour and shape. Manual identification of vegetables takes time and is prone to errors. Therefore, the automatic classification process of the precision farming, increasingly using image processing and pattern recognition to identify fruits and vegetable, is becoming essential to identify and classify vegetables in big farms. In this paper, an automatic system for the identification and classification of green leafy vegetables, similar in colour and shape was evaluataed using five different deep learning models such as CNN, MobileNet, VGG-16, Inception V3 and ResNet 50. The accuracies of these models achieved in this paper vary from 67% to 99%. The model with the highest accuracy is the MobileNet.

KW - Agriculture

KW - Deep Learning

KW - MobileNet

KW - VGG-16

KW - Vegetables Classification

UR - https://www.scopus.com/pages/publications/85172009487

U2 - 10.1109/icABCD59051.2023.10220482

DO - 10.1109/icABCD59051.2023.10220482

M3 - Conference contribution

AN - SCOPUS:85172009487

T3 - 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings

BT - 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings

A2 - Pudaruth, Sameerchand

A2 - Singh, Upasana

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023

Y2 - 3 August 2023 through 4 August 2023

ER -

Vilanculos EF, Shongwe T, Hasan AN. Identification and classification of Green Leafy Vegetables using CNN models. In Pudaruth S, Singh U, editors, 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings). doi: 10.1109/icABCD59051.2023.10220482

Identification and classification of Green Leafy Vegetables using CNN models

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this