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OpenAlex Citation Counts

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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:

Explainable Neural Network for Classification of Cotton Leaf Diseases
Javeria Amin, Muhammad Almas Anjum, Muhammad Sharif, et al.
Agriculture (2022) Vol. 12, Iss. 12, pp. 2029-2029
Open Access | Times Cited: 11

Showing 11 citing articles:

Cross-comparative review of Machine learning for plant disease detection: apple, cassava, cotton and potato plants
James Daniel Omaye, Emeka Ogbuju, Grace Ataguba, et al.
Artificial Intelligence in Agriculture (2024) Vol. 12, pp. 127-151
Open Access | Times Cited: 7
Explainable ResNet50 learning model based on copula entropy for cotton plant disease prediction
Heba Askr, M. A. El-Dosuky, Ashraf Darwish, et al.
Applied Soft Computing (2024) Vol. 164, pp. 112009-112009
Closed Access | Times Cited: 6
Performance evaluation of the classifiers based on features from cotton leaf images
Bhagya M Patil, Vishwanath Burkpalli
Multimedia Tools and Applications (2025)
Closed Access
OralNet: Fused Optimal Deep Features Framework for Oral Squamous Cell Carcinoma Detection
Ramya Mohan, Arunmozhi Rama, Ramalingam Karthik Raja, et al.
Biomolecules (2023) Vol. 13, Iss. 7, pp. 1090-1090
Open Access | Times Cited: 12
Spatial attention-based hybrid VGG-SVM and VGG-RF frameworks for improved cotton leaf disease detection
V. Pandiyaraju, B. Anusha, A. M. Senthil Kumar, et al.
Neural Computing and Applications (2025)
Closed Access
Multi-disease Classification and Severity Estimation of Cotton and Soybean Plants Using DenseNet
Vaishali G. Bhujade, V. K. Sambhe
Communications in computer and information science (2024), pp. 20-41
Closed Access | Times Cited: 1
Cotton Diseases Multiclassification: CNN and Random Forest Approach
Nisha Kumari, Tripti Mandal, Pranav Kumar, et al.
(2024) Vol. 10, pp. 71-74
Closed Access
An Intelligent Approach for Cotton Plant Disease Detection using Convolutional Neural Networks: A Deep Learning Perspective
Ritesh V. Patil Prasad Chaudhari
Deleted Journal (2024) Vol. 20, Iss. 1s, pp. 891-899
Open Access
Classification of cotton crop disease using hybrid model and MDFC feature extraction method
Padma P. Nimbhore, Ritu Tiwari, Tanmoy Hazra, et al.
Journal of Phytopathology (2024) Vol. 172, Iss. 4
Closed Access
Investigating the Feasibility of Machine Learning Models for Early Detection of Plant Diseases
Garima Joshi, Prashant Panse
(2023), pp. 289-294
Closed Access
Leveraging Spatial and Channel Attention in VGG16 for Efficient Tomato Leaf Disease Detection
Al-Momin Faruk, Hasan Al Faraby, Ahad Abdul, et al.
(2023), pp. 1-6
Closed Access
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