Curriculum Vitaes

Muhammad Nouman

  (ノマン ムハマド)

Profile Information

Affiliation
Doctoral Student, Graduate School of Information Science, University of Hyogo

ORCID ID
 https://orcid.org/0000-0002-5275-0933
J-GLOBAL ID
202401002686693269
researchmap Member ID
R000077656

Papers

 9
  • Muhammad Nouman, Mohamed Mabrok, Mohammad al-Shatouri, Essam A. Rashed
    Computers and Electrical Engineering, Jan, 2026  
  • Ghada Khoriba, Muhammad Nouman, Essam A. Rashed
    Cutting-Edge Artificial Intelligence Advances and Implications in Real-World Applications, May 16, 2025  
  • Muhammad Nouman, Mohamed Mabrok, Essam A. Rashed
    Proceedings of the 2024 9th International Conference on Multimedia and Image Processing, 152-156, Apr 20, 2024  
  • Ahsan Rehman Gill, Muhammad Azam, Muhammad Nouman
    Journal of Agricultural Research, Jun 30, 2023  
    <jats:p>Citrus is manually counted to estimate the yield. By using some innovative agricultural techniques yield and production can be increased. Numerous agricultural innovations have been introduced in recent years. Higher agricultural production, prediction, and reliable crop status information are more important than ever due to the expected growth of the human population. Agriculture has always been the foundation of human society. Current study was aimed to develop a reliable and meaningful information-gathering agricultural field based on image processing during 2020. Citrus yield can be increased in the initial stages by counting it with RGB and HSV-based images taken from an Android phone from various angles using machine learning techniques. Fertilizers such as potash, phosphorus, and nitrogen can then be utilized to boost yield. According to the findings, farmers can control and monitor citrus health production more efficiently and effectively by integrating machine learning with agriculture. The citrus calculation using the given technique compared with manually counted citrus, having difference of up to 5 to 10 citruses for a single plant per plot in a field. The proposed method produced excellent results under varying lighting conditions, leaf occlusion, and fruit overlap on photos taken at various distances from the orange trees.</jats:p>
  • Nouman, M., Azam, M., Saleh, A.M., Alsaeedi, A., Abuaddous, H.
    Bulletin of Electrical Engineering and Informatics, 12(2), 2023