Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A cucumber leaf disease severity classification method based on the fusion of DeepLabV3+ and U-Net
Chun‐Shan Wang, Pengfei Du, Huarui Wu, et al.
Computers and Electronics in Agriculture (2021) Vol. 189, pp. 106373-106373
Closed Access | Times Cited: 168

Showing 1-25 of 168 citing articles:

A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools
Aanis Ahmad, Dharmendra Saraswat, Aly El Gamal
Smart Agricultural Technology (2022) Vol. 3, pp. 100083-100083
Open Access | Times Cited: 184
Trends in vision-based machine learning techniques for plant disease identification: A systematic review
Poornima Singh Thakur, Pritee Khanna, Tanuja Sheorey, et al.
Expert Systems with Applications (2022) Vol. 208, pp. 118117-118117
Closed Access | Times Cited: 125
A two-stage deep-learning based segmentation model for crop disease quantification based on corn field imagery
L. G. Divyanth, Aanis Ahmad, Dharmendra Saraswat
Smart Agricultural Technology (2022) Vol. 3, pp. 100108-100108
Open Access | Times Cited: 73
Automatic detection and severity analysis of grape black measles disease based on deep learning and fuzzy logic
Miaomiao Ji, Zhibin Wu
Computers and Electronics in Agriculture (2022) Vol. 193, pp. 106718-106718
Closed Access | Times Cited: 72
Practical cucumber leaf disease recognition using improved Swin Transformer and small sample size
Fengyi Wang, Yuan Rao, Qing Luo, et al.
Computers and Electronics in Agriculture (2022) Vol. 199, pp. 107163-107163
Closed Access | Times Cited: 67
Tomato plant disease classification using Multilevel Feature Fusion with adaptive channel spatial and pixel attention mechanism
C. K. Sunil, Jaidhar C.D., Nagamma Patil
Expert Systems with Applications (2023) Vol. 228, pp. 120381-120381
Closed Access | Times Cited: 62
A Systematic Literature Review on Plant Disease Detection: Motivations, Classification Techniques, Datasets, Challenges, and Future Trends
Wasswa Shafik, Ali Tufail, Abdallah Namoun, et al.
IEEE Access (2023) Vol. 11, pp. 59174-59203
Open Access | Times Cited: 53
Systematic study on deep learning-based plant disease detection or classification
C. K. Sunil, C. D. Jaidhar, Nagamma Patil
Artificial Intelligence Review (2023) Vol. 56, Iss. 12, pp. 14955-15052
Closed Access | Times Cited: 48
Plant image recognition with deep learning: A review
Huiling Chen, Yiqi Huang, Zizhao Zhang, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108072-108072
Closed Access | Times Cited: 48
Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations
Abbas Jafar, N. Bibi, Rizwan Ali Naqvi, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 48
An Effective Image-Based Tomato Leaf Disease Segmentation Method Using MC-UNet
Yubao Deng, Haoran Xi, Guoxiong Zhou, et al.
Plant Phenomics (2023) Vol. 5
Open Access | Times Cited: 39
Cucumber Leaf Diseases Recognition Using Multi Level Deep Entropy-ELM Feature Selection
Muhammad Attique Khan, Abdullah Alqahtani, Aimal Khan, et al.
Applied Sciences (2022) Vol. 12, Iss. 2, pp. 593-593
Open Access | Times Cited: 59
LEMOXINET: Lite ensemble MobileNetV2 and Xception models to predict plant disease
Deni Sutaji, Oktay Yıldız
Ecological Informatics (2022) Vol. 70, pp. 101698-101698
Closed Access | Times Cited: 54
An Improved DeepLab v3+ Deep Learning Network Applied to the Segmentation of Grape Leaf Black Rot Spots
Hongbo Yuan, Jiajun Zhu, Qifan Wang, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 43
MobiRes-Net: A Hybrid Deep Learning Model for Detecting and Classifying Olive Leaf Diseases
Amel Ksibi, Manel Ayadi, Ben Othman Soufiene, et al.
Applied Sciences (2022) Vol. 12, Iss. 20, pp. 10278-10278
Open Access | Times Cited: 41
A novel approach for apple leaf disease image segmentation in complex scenes based on two-stage DeepLabv3+ with adaptive loss
Shisong Zhu, Wanli Ma, Jiangwen Lu, et al.
Computers and Electronics in Agriculture (2022) Vol. 204, pp. 107539-107539
Closed Access | Times Cited: 39
A sugar beet leaf disease classification method based on image processing and deep learning
Kemal Adem, Mehmet Metin Özgüven, Ziya Altaş
Multimedia Tools and Applications (2022) Vol. 82, Iss. 8, pp. 12577-12594
Closed Access | Times Cited: 37
Detecting Severity Levels of Cucumber Leaf Spot Disease using ResNext Deep Learning Model: A Digital Image Analysis Approach
Ankit Bansal, Rishabh Sharma, Vikrant Sharma, et al.
(2023) Vol. 24, pp. 1-6
Closed Access | Times Cited: 26
Computer Vision for Plant Disease Recognition: A Comprehensive Review
Minh Hoang Dang, Hanxiang Wang, Yanfen Li, et al.
The Botanical Review (2024) Vol. 90, Iss. 3, pp. 251-311
Closed Access | Times Cited: 10
Rice disease segmentation method based on CBAM-CARAFE-DeepLabv3+
Wei Zeng, Mingfang He
Crop Protection (2024) Vol. 180, pp. 106665-106665
Closed Access | Times Cited: 9
Apple Leaf Disease Identification with a Small and Imbalanced Dataset Based on Lightweight Convolutional Networks
Lili Li, Shujuan Zhang, Bin Wang
Sensors (2021) Vol. 22, Iss. 1, pp. 173-173
Open Access | Times Cited: 49
Two-Stage Convolutional Neural Networks for Diagnosing the Severity of Alternaria Leaf Blotch Disease of the Apple Tree
Boyuan Liu, Ke-Jun Fan, Wen‐Hao Su, et al.
Remote Sensing (2022) Vol. 14, Iss. 11, pp. 2519-2519
Open Access | Times Cited: 33
Maize Small Leaf Spot Classification Based on Improved Deep Convolutional Neural Networks with a Multi-Scale Attention Mechanism
Chenghai Yin, Tiwei Zeng, Huiming Zhang, et al.
Agronomy (2022) Vol. 12, Iss. 4, pp. 906-906
Open Access | Times Cited: 31
Detection and Counting of Maize Leaves Based on Two-Stage Deep Learning with UAV-Based RGB Image
Xingmei Xu, Lu Wang, Meiyan Shu, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5388-5388
Open Access | Times Cited: 30
The Detection Method of Potato Foliage Diseases in Complex Background Based on Instance Segmentation and Semantic Segmentation
Xudong Li, Yuhong Zhou, Jingyan Liu, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 27
Page 1 - Next Page

Scroll to top