An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases

Monica Uttarwar; Girija Chetty; Mohammad Yamin; Matthew White

doi:10.1109/CSDE59766.2023.10487697

An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases

Monica Uttarwar, Girija Chetty, Mohammad Yamin, Matthew White

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

In this paper a novel deep learning model for detection of plant leaf disease and agricultural pests. The proposed integreated hybrid model development based on EfficientNetB0 deep learning architecture allows model deployment in low resource settings with limited training data, allowing new and rare plant diseases and agricultural pests to be detected accurately.

Original language	English
Title of host publication	Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-6
Number of pages	6
ISBN (Electronic)	9798350341072
ISBN (Print)	9798350341089
DOIs	https://doi.org/10.1109/CSDE59766.2023.10487697
Publication status	Published - 6 Dec 2023
Event	2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) - Yanuca Island, Fiji Duration: 4 Dec 2023 → 6 Dec 2023 https://ieee-csde.org/csde2023/

Publication series

Name	Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023

Conference

Conference	2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)
Country/Territory	Fiji
Period	4/12/23 → 6/12/23
Internet address	https://ieee-csde.org/csde2023/

UN SDGs

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

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10.1109/CSDE59766.2023.10487697

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10487697

Cite this

Uttarwar, M., Chetty, G., Yamin, M., & White, M. (2023). An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases. In Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023 (pp. 1-6). Article 10487697 (Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CSDE59766.2023.10487697

Uttarwar, Monica ; Chetty, Girija ; Yamin, Mohammad et al. / An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases. Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023. IEEE, Institute of Electrical and Electronics Engineers, 2023. pp. 1-6 (Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023).

@inproceedings{6f648ba273b2433ea7da63a1061b160a,

title = "An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases",

abstract = "In this paper a novel deep learning model for detection of plant leaf disease and agricultural pests. The proposed integreated hybrid model development based on EfficientNetB0 deep learning architecture allows model deployment in low resource settings with limited training data, allowing new and rare plant diseases and agricultural pests to be detected accurately.",

keywords = "Deep learning, Computer science, Plant diseases, Plants (biology), Computational modeling, Training data, Data engineering, deep learning, agricultural pests, plant leaf diseases",

author = "Monica Uttarwar and Girija Chetty and Mohammad Yamin and Matthew White",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) ; Conference date: 04-12-2023 Through 06-12-2023",

year = "2023",

month = dec,

day = "6",

doi = "10.1109/CSDE59766.2023.10487697",

language = "English",

isbn = "9798350341089",

series = "Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

pages = "1--6",

booktitle = "Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023",

address = "United States",

url = "https://ieee-csde.org/csde2023/",

}

Uttarwar, M, Chetty, G, Yamin, M & White, M 2023, An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases. in Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023., 10487697, Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023, IEEE, Institute of Electrical and Electronics Engineers, pp. 1-6, 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Fiji, 4/12/23. https://doi.org/10.1109/CSDE59766.2023.10487697

An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases. / Uttarwar, Monica; Chetty, Girija; Yamin, Mohammad et al.
Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023. IEEE, Institute of Electrical and Electronics Engineers, 2023. p. 1-6 10487697 (Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

TY - GEN

T1 - An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases

AU - Uttarwar, Monica

AU - Chetty, Girija

AU - Yamin, Mohammad

AU - White, Matthew

PY - 2023/12/6

Y1 - 2023/12/6

N2 - In this paper a novel deep learning model for detection of plant leaf disease and agricultural pests. The proposed integreated hybrid model development based on EfficientNetB0 deep learning architecture allows model deployment in low resource settings with limited training data, allowing new and rare plant diseases and agricultural pests to be detected accurately.

AB - In this paper a novel deep learning model for detection of plant leaf disease and agricultural pests. The proposed integreated hybrid model development based on EfficientNetB0 deep learning architecture allows model deployment in low resource settings with limited training data, allowing new and rare plant diseases and agricultural pests to be detected accurately.

KW - Deep learning

KW - Computer science

KW - Plant diseases

KW - Plants (biology)

KW - Computational modeling

KW - Training data

KW - Data engineering

KW - deep learning

KW - agricultural pests

KW - plant leaf diseases

UR - https://ieeexplore.ieee.org/document/10487697/

UR - http://www.scopus.com/inward/record.url?scp=85190614169&partnerID=8YFLogxK

UR - https://ieeexplore.ieee.org/xpl/conhome/10487636/proceeding

UR - https://ieee-csde.org/csde2023/

U2 - 10.1109/CSDE59766.2023.10487697

DO - 10.1109/CSDE59766.2023.10487697

M3 - Conference contribution

SN - 9798350341089

T3 - Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023

SP - 1

EP - 6

BT - Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)

Y2 - 4 December 2023 through 6 December 2023

ER -

Uttarwar M, Chetty G, Yamin M, White M. An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases. In Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023. IEEE, Institute of Electrical and Electronics Engineers. 2023. p. 1-6. 10487697. (Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023). doi: 10.1109/CSDE59766.2023.10487697

An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases

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