ARCHIVES

1. Mudassir Iftikhar, Irfan Ali Kandhro, Neha Kausar, et al., “Plant disease management: a fine-tuned enhanced CNN approach with
mobile app integration for early detection and classification,” Artificial Intelligence Review, vol. 57, 2024.
2. Archana Buddham Pahurkar and Ravindra Madhukarrao Deshmukh, “SMoGW-based deep CNN: Plant disease detection and
classification using SMoGW-deep CNN classifier,” Web Intelligence, 2023.
3. Tingting Shi, Yongmin Liu, Xinying Zheng, et al., “Recent advances in plant disease severity assessment using convolutional neural
networks,” Scientific Reports, vol. 13, 2023.
4. Wubetu Barud Demilie, “Plant disease detection and classification techniques: a comparative study of the performances,” Journal of
Big Data, vol. 11, 2024.
5. Payam Delfani, Vishnukiran Thuraga, Bikram Banerjee, et al., “Integrative approaches in modern agriculture: IoT, ML and AI for
disease forecasting amidst climate change,” Precision Agriculture, vol. 25, 2024.
6. Harry Rogers, Beatriz De La Iglesia, Tahmina Zebin, et al., “Advancing precision agriculture: domain-specific augmentations and
robustness testing for convolutional neural networks in precision spraying evaluation,” Neural Computing and Applications, vol. 36,
2024.
7. “Field evaluation of a deep learning-based smart variable-rate sprayer for targeted application of agrochemicals,” Smart Agricultural
Technology, vol. 3, 2023.
8. “Next generation of computer vision for plant disease monitoring in precision agriculture: A contemporary survey, taxonomy,
experiments, and future direction,” Information Sciences, vol. 665, 2024.
9. Shkelqim Sherifi, "A Compact and Efficient 1.251 Million Parameter Machine Learning CNN Model PD36-C for Plant Disease
Detection: A Case Study," arXiv preprint arXiv:2604.11332, 2026.
10. Affan Yasin and Rubia Fatima, "On the Image-Based Detection of Tomato and Corn Leaves Diseases: An In-Depth Comparative
Experiments," arXiv preprint arXiv:2312.08659, 2023.
11. Sourish Suri and Yifei Shao, "Automated Multi-Class Crop Pathology Classification via Convolutional Neural Networks: A Deep
Learning Approach for Real-Time Precision Agriculture," arXiv preprint arXiv:2507.09375, 2025.
12. Andre S. Abade, Paulo Afonso Ferreira, and Flavio de Barros Vidal, "Plant Diseases Recognition on Images Using Convolutional
Neural Networks: A Systematic Review," arXiv preprint arXiv:2009.04365, 2020.
13. Abhishek Upadhyay, Narendra Singh Chandel, Krishna Pratap Singh, et al., "Deep Learning and Computer Vision in Plant Disease
Detection: A Comprehensive Review of Techniques, Models, and Trends in Precision Agriculture," Artificial Intelligence Review, vol.
58, 2025.
14. Vijaypal Singh Dhaka, Nidhi Kundu, Geeta Rani, et al., "Role of Internet of Things and Deep Learning Techniques in Plant Disease
Detection and Classification: A Focused Review," Sensors, vol. 23, no.18, 2023.
15. W. Shafik, A. Tufail, A. Namoun, et al., "A Systematic Literature Review on Plant Disease Detection: Motivations, Classificat ion
Techniques, Datasets, Challenges, and Future Trends," IEEE Access, vol.11, 2023.
16. M. Ramanjot et al., "Plant Disease Detection and Classification: A Systematic Literature Review," Sensors, vol.23, no.10, 2023.
17. Sana Parez, Naqqash Dilshad, Norah Saleh Alghamdi, et al., "Visual Intelligence in Precision Agriculture: Exploring Plant Disease
Detection via Efficient Vision Transformers," Sensors, vol.23, no.15, 2023.
18. Pulicherla Siva Prasad and Senthilrajan Agniraj, "C-MAN: A Multi-attention Approach for Precise Plant Species Classification and
Disease Detection Using Multi-scale, Channel-wise and Cross-modal Attentions," Traitement du Signal, vol.41, no.3, 2024..
19. Srinivas Kanakala and Sneha Ningappa, “Disease Detection and Classification on Multi-Crop Leaves Using LSTM and CNN Model,”
arXiv Preprint, 2025.
20. Sourish Suri and Yifei Shao, “Multi-Class Automated Crop Pathology Classification Using Convolutional Neural Networks: A Deep
Learning Approach,” arXiv Preprint, 2025.