Dr. Seyed Mohamad Javidan | Plant Disease Detection | Best Researcher Award
Dr. Seyed Mohamad Javidan, Tarbiat Modares University, Iran
Dr. Seyed Mohamad Javidan is a dedicated researcher and educator in Biosystems Engineering at Tarbiat Modares University, Tehran, Iran. He earned his PhD in 2023 with a focus on diagnosing tomato fungal diseases through image processing. His research interests include plant disease detection, precision agriculture, and biosensor technologies. Dr. Javidan holds several patents, including innovations in agricultural machinery. He has published numerous articles in reputable journals and actively participates in conferences. Fluent in English and Farsi, he also teaches automotive engineering courses, fostering the next generation of engineers. šš¾
Publication profile
Education
Research Interests
Awards and Recognitions
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Conclusion
Dr. Seyed Mohamad Javidan’s extensive educational background, impactful research contributions, innovative patents, and commitment to teaching and mentoring position him as an exceptional candidate for the Best Researcher Award. His work not only advances academic knowledge but also addresses practical challenges in agriculture, making a significant impact on the field.
Publication Top Notes
- Diagnosis of grape leaf diseases using automatic K-means clustering and machine learning š± ā Cited by: 120, Year: 2023
- Tomato leaf diseases classification using image processing and weighted ensemble learning š ā Cited by: 16, Year: 2024
- Design, construction and evaluation of semi-automatic vegetable transplanter with conical distributor cup š ļø ā Cited by: 13, Year: 2019
- A feature selection method using slime mould optimization algorithm in order to diagnose plant leaf diseases š ā Cited by: 12, Year: 2022
- Detection of Cucumber Fruit on Plant Images Using Artificial Neural Network š„ ā Cited by: 12, Year: 2022
- Detection of Callosobruchus maculatus F. with image processing and artificial neural network š ā Cited by: 10*, Year: 2020
- Diagnosing the spores of tomato fungal diseases using microscopic image processing and machine learning šæ ā Cited by: 9, Year: 2024
- Design, Construction, and Evaluation of Automated Seeder with Ultrasonic Sensors for Row Detection š ā Cited by: 8, Year: 2021
- A novel approach for automated strawberry fruit varieties classification using image processing and machine learning š ā Cited by: 4, Year: 2024
- Design and construction of solar seeding robot equipped with row detection technology āļø ā Cited by: 3, Year: 2018