A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture

Syed I. Moazzam; Umar Shahbaz Khan; Mohsin Islam Tiwana; Javed Iqbal; Waqar S. Qureshi; Syed Irfan Shah

doi:10.1109/ICRAI47710.2019.8967350

A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture

Syed I. Moazzam, Umar Shahbaz Khan, Mohsin Islam Tiwana, Javed Iqbal, Waqar S. Qureshi, Syed Irfan Shah

National University of Sciences and Technology Pakistan

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

25 Citations (Scopus)

Abstract

Weeds are major cause due to which farmers get poor harvest of crops. Many algorithms are developed to classify weeds from crops to autonomously destroy weeds. Color-based, threshold-based and learning-based techniques are deployed in the past. From all techniques, deep-learning-based techniques stand out by showing the best performances. In this paper, deeplearning-based techniques are reviewed in the case where these are applied for weed detection in agricultural crops. Sunflower, carrot, soybean, sugar beet and maize are reviewed with respect to the weeds present in them. Deep learning structures and parameters are presented, and research Gaps are identified for further research.

Original language	English
Title of host publication	2019 International Conference on Robotics and Automation in Industry, ICRAI 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728130583
DOIs	https://doi.org/10.1109/ICRAI47710.2019.8967350
Publication status	Published - Oct 2019
Externally published	Yes
Event	3rd International Conference on Robotics and Automation in Industry, ICRAI 2019 - Rawalpindi, Pakistan Duration: 21 Oct 2019 → 22 Oct 2019

Publication series

Name	2019 International Conference on Robotics and Automation in Industry, ICRAI 2019

Conference

Conference	3rd International Conference on Robotics and Automation in Industry, ICRAI 2019
Country/Territory	Pakistan
City	Rawalpindi
Period	21/10/19 → 22/10/19

Keywords

Convolutional Neural Networks
Deep learning
Image processing
Precision agriculture
Smart farming
Weed detection

Access to Document

10.1109/ICRAI47710.2019.8967350

Cite this

Moazzam, S. I., Khan, U. S., Tiwana, M. I., Iqbal, J., Qureshi, W. S., & Shah, S. I. (2019). A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture. In 2019 International Conference on Robotics and Automation in Industry, ICRAI 2019 Article 8967350 (2019 International Conference on Robotics and Automation in Industry, ICRAI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRAI47710.2019.8967350

Moazzam, Syed I. ; Khan, Umar Shahbaz ; Tiwana, Mohsin Islam et al. / A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture. 2019 International Conference on Robotics and Automation in Industry, ICRAI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 International Conference on Robotics and Automation in Industry, ICRAI 2019).

@inproceedings{ce41bf1a4d224c68886fecf9f69e935c,

title = "A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture",

abstract = "Weeds are major cause due to which farmers get poor harvest of crops. Many algorithms are developed to classify weeds from crops to autonomously destroy weeds. Color-based, threshold-based and learning-based techniques are deployed in the past. From all techniques, deep-learning-based techniques stand out by showing the best performances. In this paper, deeplearning-based techniques are reviewed in the case where these are applied for weed detection in agricultural crops. Sunflower, carrot, soybean, sugar beet and maize are reviewed with respect to the weeds present in them. Deep learning structures and parameters are presented, and research Gaps are identified for further research.",

keywords = "Convolutional Neural Networks, Deep learning, Image processing, Precision agriculture, Smart farming, Weed detection",

author = "Moazzam, {Syed I.} and Khan, {Umar Shahbaz} and Tiwana, {Mohsin Islam} and Javed Iqbal and Qureshi, {Waqar S.} and Shah, {Syed Irfan}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 3rd International Conference on Robotics and Automation in Industry, ICRAI 2019 ; Conference date: 21-10-2019 Through 22-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ICRAI47710.2019.8967350",

language = "English",

series = "2019 International Conference on Robotics and Automation in Industry, ICRAI 2019",

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

booktitle = "2019 International Conference on Robotics and Automation in Industry, ICRAI 2019",

}

Moazzam, SI, Khan, US, Tiwana, MI, Iqbal, J, Qureshi, WS & Shah, SI 2019, A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture. in 2019 International Conference on Robotics and Automation in Industry, ICRAI 2019., 8967350, 2019 International Conference on Robotics and Automation in Industry, ICRAI 2019, Institute of Electrical and Electronics Engineers Inc., 3rd International Conference on Robotics and Automation in Industry, ICRAI 2019, Rawalpindi, Pakistan, 21/10/19. https://doi.org/10.1109/ICRAI47710.2019.8967350

A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture. / Moazzam, Syed I.; Khan, Umar Shahbaz; Tiwana, Mohsin Islam et al.
2019 International Conference on Robotics and Automation in Industry, ICRAI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8967350 (2019 International Conference on Robotics and Automation in Industry, ICRAI 2019).

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

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AU - Moazzam, Syed I.

AU - Khan, Umar Shahbaz

AU - Tiwana, Mohsin Islam

AU - Iqbal, Javed

AU - Qureshi, Waqar S.

AU - Shah, Syed Irfan

PY - 2019/10

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AB - Weeds are major cause due to which farmers get poor harvest of crops. Many algorithms are developed to classify weeds from crops to autonomously destroy weeds. Color-based, threshold-based and learning-based techniques are deployed in the past. From all techniques, deep-learning-based techniques stand out by showing the best performances. In this paper, deeplearning-based techniques are reviewed in the case where these are applied for weed detection in agricultural crops. Sunflower, carrot, soybean, sugar beet and maize are reviewed with respect to the weeds present in them. Deep learning structures and parameters are presented, and research Gaps are identified for further research.

KW - Convolutional Neural Networks

KW - Deep learning

KW - Image processing

KW - Precision agriculture

KW - Smart farming

KW - Weed detection

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DO - 10.1109/ICRAI47710.2019.8967350

M3 - Conference contribution

AN - SCOPUS:85079216101

T3 - 2019 International Conference on Robotics and Automation in Industry, ICRAI 2019

BT - 2019 International Conference on Robotics and Automation in Industry, ICRAI 2019

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 21 October 2019 through 22 October 2019

ER -

Moazzam SI, Khan US, Tiwana MI, Iqbal J, Qureshi WS, Shah SI. A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture. In 2019 International Conference on Robotics and Automation in Industry, ICRAI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8967350. (2019 International Conference on Robotics and Automation in Industry, ICRAI 2019). doi: 10.1109/ICRAI47710.2019.8967350

A Review of Application of Deep Learning for Weeds and Crops Classification in Agriculture

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