Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest

Agus Wahyu Widodo; Alfita Rakhmandasari; Wayan Firdaus Mahmudy; Muh Arif Rahman; Diva Kurnianingtyas

doi:10.1145/3626641.3626664

Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest

Faculty of Computer Science

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

Abstract

The Kenaf plant is a source of natural fibre and can potentially be a source of bioenergy, biopharmaceuticals, bioremediation, and others. The need for Kenaf plant fibre is increasing due to the variety of plant uses. This high demand is different from a high production level as well. One of the main production barriers is pests and diseases in plants. Rapid detection of pests and diseases is needed to carry out appropriate actions. Pest and disease detection can be assisted with deep learning methods such as Single-Shot Multibox Detection (SSD) Mobilenet. Data augmentation is carried out to improve the accuracy of the results. Although the Mobilenet SSD gets an accuracy of only 54%, using data augmentation can increase the accuracy of the Mobilenet SSD by 14.02% to 72.02%. This result is better than using Faster Region-based Convolutional Neural Network (RCNN), which is used as a comparison method.

Original language	English
Title of host publication	SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology
Publisher	Association for Computing Machinery
Pages	45-50
Number of pages	6
ISBN (Electronic)	9798400708503
DOIs	https://doi.org/10.1145/3626641.3626664
Publication status	Published - 24 Oct 2023
Event	8th International Conference on Sustainable Information Engineering and Technology, SIET 2023 - Bali, Indonesia Duration: 24 Oct 2023 → 25 Oct 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	8th International Conference on Sustainable Information Engineering and Technology, SIET 2023
Country/Territory	Indonesia
City	Bali
Period	24/10/23 → 25/10/23

UN SDGs

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

SDG 7 Affordable and Clean Energy
SDG 15 Life on Land

Keywords

Convolutional neural network
Data augmentation
Deep learning
Kenaf plant
Single-Shot Multibox Detection (SSD) Mobilnet

Access to Document

10.1145/3626641.3626664

Cite this

Widodo, A. W., Rakhmandasari, A., Mahmudy, W. F., Rahman, M. A., & Kurnianingtyas, D. (2023). Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest. In SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology (pp. 45-50). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3626641.3626664

Widodo, Agus Wahyu ; Rakhmandasari, Alfita ; Mahmudy, Wayan Firdaus et al. / Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest. SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology. Association for Computing Machinery, 2023. pp. 45-50 (ACM International Conference Proceeding Series).

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title = "Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest",

abstract = "The Kenaf plant is a source of natural fibre and can potentially be a source of bioenergy, biopharmaceuticals, bioremediation, and others. The need for Kenaf plant fibre is increasing due to the variety of plant uses. This high demand is different from a high production level as well. One of the main production barriers is pests and diseases in plants. Rapid detection of pests and diseases is needed to carry out appropriate actions. Pest and disease detection can be assisted with deep learning methods such as Single-Shot Multibox Detection (SSD) Mobilenet. Data augmentation is carried out to improve the accuracy of the results. Although the Mobilenet SSD gets an accuracy of only 54\%, using data augmentation can increase the accuracy of the Mobilenet SSD by 14.02\% to 72.02\%. This result is better than using Faster Region-based Convolutional Neural Network (RCNN), which is used as a comparison method.",

keywords = "Convolutional neural network, Data augmentation, Deep learning, Kenaf plant, Single-Shot Multibox Detection (SSD) Mobilnet",

author = "Widodo, \{Agus Wahyu\} and Alfita Rakhmandasari and Mahmudy, \{Wayan Firdaus\} and Rahman, \{Muh Arif\} and Diva Kurnianingtyas",

note = "Publisher Copyright: {\textcopyright} 2023 ACM.; 8th International Conference on Sustainable Information Engineering and Technology, SIET 2023 ; Conference date: 24-10-2023 Through 25-10-2023",

year = "2023",

month = oct,

day = "24",

doi = "10.1145/3626641.3626664",

language = "English",

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Widodo, AW, Rakhmandasari, A, Mahmudy, WF , Rahman, MA & Kurnianingtyas, D 2023, Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest. in SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 45-50, 8th International Conference on Sustainable Information Engineering and Technology, SIET 2023, Bali, Indonesia, 24/10/23. https://doi.org/10.1145/3626641.3626664

Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest. / Widodo, Agus Wahyu; Rakhmandasari, Alfita; Mahmudy, Wayan Firdaus et al.
SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology. Association for Computing Machinery, 2023. p. 45-50 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest

AU - Widodo, Agus Wahyu

AU - Rakhmandasari, Alfita

AU - Mahmudy, Wayan Firdaus

AU - Rahman, Muh Arif

AU - Kurnianingtyas, Diva

PY - 2023/10/24

Y1 - 2023/10/24

N2 - The Kenaf plant is a source of natural fibre and can potentially be a source of bioenergy, biopharmaceuticals, bioremediation, and others. The need for Kenaf plant fibre is increasing due to the variety of plant uses. This high demand is different from a high production level as well. One of the main production barriers is pests and diseases in plants. Rapid detection of pests and diseases is needed to carry out appropriate actions. Pest and disease detection can be assisted with deep learning methods such as Single-Shot Multibox Detection (SSD) Mobilenet. Data augmentation is carried out to improve the accuracy of the results. Although the Mobilenet SSD gets an accuracy of only 54%, using data augmentation can increase the accuracy of the Mobilenet SSD by 14.02% to 72.02%. This result is better than using Faster Region-based Convolutional Neural Network (RCNN), which is used as a comparison method.

AB - The Kenaf plant is a source of natural fibre and can potentially be a source of bioenergy, biopharmaceuticals, bioremediation, and others. The need for Kenaf plant fibre is increasing due to the variety of plant uses. This high demand is different from a high production level as well. One of the main production barriers is pests and diseases in plants. Rapid detection of pests and diseases is needed to carry out appropriate actions. Pest and disease detection can be assisted with deep learning methods such as Single-Shot Multibox Detection (SSD) Mobilenet. Data augmentation is carried out to improve the accuracy of the results. Although the Mobilenet SSD gets an accuracy of only 54%, using data augmentation can increase the accuracy of the Mobilenet SSD by 14.02% to 72.02%. This result is better than using Faster Region-based Convolutional Neural Network (RCNN), which is used as a comparison method.

KW - Convolutional neural network

KW - Data augmentation

KW - Deep learning

KW - Kenaf plant

KW - Single-Shot Multibox Detection (SSD) Mobilnet

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M3 - Conference contribution

AN - SCOPUS:85182397768

T3 - ACM International Conference Proceeding Series

SP - 45

EP - 50

BT - SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology

PB - Association for Computing Machinery

T2 - 8th International Conference on Sustainable Information Engineering and Technology, SIET 2023

Y2 - 24 October 2023 through 25 October 2023

ER -

Widodo AW, Rakhmandasari A, Mahmudy WF , Rahman MA , Kurnianingtyas D. Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest. In SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology. Association for Computing Machinery. 2023. p. 45-50. (ACM International Conference Proceeding Series). doi: 10.1145/3626641.3626664

Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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