Automated masks generation for coffee and apple leaf infected with single or multiple diseases-based color analysis approaches

Informatics in Medicine Unlocked - Tập 28 - Trang 100837 - 2022
Reem Ibrahim Hasan1,2, Suhaila Mohd Yusuf1, Mohd Shafry Mohd Rahim1, Laith Alzubaidi3,4
1School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai, Johor, 81310, Malaysia
2Al-Nidhal Campus, University of Information Technology & Communications, Baghdad, 00964, Iraq
3Faculty of Science & Engineering, Queensland University of Technology, Brisbane, QLD, 4000, Australia
4School of Engineering, Architecture and Information Technology, The University of Queensland, Brisbane, QLD, 4000, Australia

Tài liệu tham khảo

Roth, 2018, Deep learning and its application to medical image segmentation, Med imaging Technol, 36, 63

I. R. I. Haque, J. Neubert (2020).

Amara, 2017, A deep learning-based approach for Banana leaf diseases classification, vol. 266, 79

Zhang, 2019, Three-channel convolutional neural networks for vegetable leaf disease recognition, Cognit Syst Res, 53, 31, 10.1016/j.cogsys.2018.04.006

Ngugi, 2020, Recent advances in image processing techniques for automated leaf pest and disease recognition-A review, Inf. Process. Agric, 8(1), 27

Sorte, 2019, Coffee leaf disease recognition based on deep learning and texture attributes, Procedia Comput Sci, 159, 135, 10.1016/j.procs.2019.09.168

Shin, 2020, Effect of directional augmentation using supervised machine learning technologies: a case study of strawberry powdery mildew detection, Biosyst Eng, 194, 49, 10.1016/j.biosystemseng.2020.03.016

Sood, 2020, Hybrid system for detection and classification of plant disease using qualitative texture features analysis, Procedia Comput Sci, 1056

Sinha, 2020, Olive spot disease detection and classification using analysis of leaf image textures, Procedia Comput Sci, 167, 2328, 10.1016/j.procs.2020.03.285

M. Sharif, M. A. Khan, Z. Iqbal, M. F. Azam, M. I. Lali (2018).

Khan, 2018, Ccdf, 155, 220

A. A. Yahya, J. Tan, . B. Su, M. Hu, Y. Wang, K. Liu, A. Hadi.

Marcos, 2019, Coffee leaf rust detection using convolutional neural network, 38

Barbedo, 2019, Plant disease identification from individual lesions and spots using deep learning, Biosyst Eng, 180, 96, 10.1016/j.biosystemseng.2019.02.002

J. G. Esgario, P. B. D. Castro, L. M. Tassis, R. A. Krohling (2021).

Tekkesinoglu, 2014, Hevea leaves boundary identification based on morphological transformation and edge detection features, Res J Appl Sci Eng Technol, 7, 2447, 10.19026/rjaset.7.551

Fern, 2017, Stratified classification of plant species based on venation state, Biomed Res, 5660

Fern, 2014, Leaf recognition based on leaf tip and leaf base using centroid contour gradient, Adv Sci Lett, 20, 209, 10.1166/asl.2014.5300

Kolivand, 2019, A new leaf venation detection technique for plant species classification, Arabian J Sci Eng, 44, 3315, 10.1007/s13369-018-3504-8

Kolivand, 2018, An expert botanical feature extraction technique based on phenetic features for identifying plant species, PLoS One, 10.1371/journal.pone.0191447

Tian, 2019, Segmentation of tomato leaf images based on adaptive clustering number of K-means algorithm, Comput Electron Agric, 165, 10.1016/j.compag.2019.104962

G. L. Manso, H. Knidel, R. A. Krohling, J. A. Ventura (2019).

Malik, 2016, Detection and counting of on-tree citrus fruit for crop yield estimation, Int J Adv Comput Sci Appl, 7

A. E. Rad, M. S. M. Rahim, H. Kolivand (2017).

Gurrala, 2019, A new segmentation method for plant disease diagnosis, 137

Tetila, 2020, Automatic recognition of soybean leaf diseases using UAV images and deep convolutional neural networks, Geosci Rem Sens Lett IEEE, 17, 903, 10.1109/LGRS.2019.2932385

P. Sharma, Y. P. S. Berwal, W. Ghai.

Kuznetsova, 2020, Using YOLOv3 algorithm with pre-and post-processing for apple detection in fruit-harvesting robot, Agronomy, 10.3390/agronomy10071016

J. Chen, Q. Liu, L. Gao (2019).

E. L. Stewart, T. Wiesner-Hanks, N. Kaczmar, C. Dechant, H. Wu, H. Lipson, M. A. Gore (2019).

Liu, 2021, Plant diseases and pests detection based on deep learning: a review, Plant Methods, 1

Hasan, 2020, Review of the state of the art of deep learning for plant diseases: a broad analysis and discussion, Plants, 9, 10.3390/plants9101302

Juliano, 2021, Deep learning architectures for semantic segmentation and automatic estimation of severity of foliar symptoms caused by diseases or pests, Biosyst Eng, 210, 129, 10.1016/j.biosystemseng.2021.08.011

J. G. Esgario, R. A. Krohling, J. A. Ventura (2020).

J. Parraga-Alava, K. Cusme, A. Loor, E. Santander (2019).

Son, 2021, Leaf spot attention networks based on spot feature encoding for leaf disease identification and detection, Appl Sci

Rother, 2004, GrabCut" interactive foreground extraction using iterated graph cuts, ACM Trans Graph, 23, 309, 10.1145/1015706.1015720

Hou, 2021, Recognition of early blight and late blight diseases on potato leaves based on graph cut segmentation, Journal of Agriculture and Food Research, 5, 10.1016/j.jafr.2021.100154

A. M. Abdu, M. M. Mokji, U. U. Sheikh (2020).

Yu, 2020, Apple leaf disease identification through region-of-interest-aware deep convolutional neural network, J Imag Sci Technol, 20507

Thông tin
Thông tin xuất bản

Informatics in Medicine Unlocked

Tập 28

100837

Thông tin tác giả