Best Researcher Award
Shaik Salma Asiya Begum — Lakireddy Bali Reddy College of Engineering, India.
Shaik Salma Asiya Begum is a researcher whose documented scholarly activities include machine learning, intelligent systems, plant disease recognition, image classification, and computational approaches to agricultural applications. Her record identifies and records academic employment and qualifications in computer science and engineering. [1]
Abstract
The Best Researcher Award recognition profile presents documented scholarly activities associated with Shaik Salma Asiya Begum, with particular emphasis on machine learning and intelligent computational applications. The ORCID record lists eight works, including journal articles, a book chapter, and a conference paper addressing agricultural image recognition, disease classification, optimization, and vehicular networking. [1]
Keywords
Machine Learning; Artificial Intelligence; Image Classification; Plant Disease Detection; Deep Learning; Computer Vision; Optimization; Precision Agriculture; Intelligent Systems; Vehicular Ad Hoc Networks.
Introduction
Shaik Salma Asiya Begum’s recorded academic background is rooted in computer science and engineering, including B.Tech. and M.Tech. qualifications in CSE. Her employment history records assistant-professor positions at MVR College of Engineering and Technology and NOVA College of Engineering and Technology, as well as a later assistant-professor position in Andhra Pradesh. [1]
Research Profile
The research profile represented in the record includes machine-learning methods for image recognition and classification, particularly applications involving pepper, maize, and other food-crop diseases. Other documented research concerns artificial neural networks, vehicular environments, and intelligent frameworks for data-driven precision agriculture and sustainable resource management. [2]
Research Contributions
The research contributions of Shaik Salma Asiya Begum include machine-learning and deep-learning approaches for image recognition, classification, and plant disease identification. Additional research includes ANN-based routing protocols for vehicular environments and data-driven frameworks supporting precision agriculture and sustainable resource management. [2]
Publications
The Research record identifies publications including “CSIU-Net+: Pepper and corn leaves classification and severity identification using hybrid optimization,” published in Environmental Research Communications, and “GSAtt-CMNetV3: Pepper Leaf Disease Classification Using Osprey Optimization,” published in IEEE Access. It also records work on unsupervised deep learning for plant disease and pest identification and an ANN-based routing study. [3]
Research Impact
The researcher information reports 18 documents, 166 citations, and an h-index of 5 in the stated profile data. The ORCID record also documents peer-review activity for multiple journals and identifies 15 reviews across seven publications or grants, providing additional evidence of participation in scholarly peer review. [1]
Award Suitability
The documented research record provides subject-matter evidence relevant to a researcher-recognition profile in machine learning. The listed publications cover computational intelligence, image classification, optimization, and intelligent systems, while the recorded review activity demonstrates engagement with scholarly evaluation. Final award eligibility remains subject to the official criteria of the Scientific World Research Awards. [5]
Conclusion
Shaik Salma Asiya Begum’s documented profile combines computer-science education, machine-learning research, agricultural image-analysis studies, intelligent-networking research, publications, and peer-review activity. These records provide a structured academic basis for presenting her research profile in connection with the Best Researcher Award at the Scientific World Research Awards. [1]
External Links
References
- ORCID. (2026). Dr. Shaik Salma Asiya Begum, ORCID record 0000-0002-5616-3963. ORCID.
https://orcid.org/0000-0002-5616-3963
- Elsevier. (n.d.). Scopus Author Profile: Shaik Salma Asiya Begum, Author ID 57210980130. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57210980130
- Begum, S. S. A., & Syed, H. (2024). GSAtt-CMNetV3: Pepper Leaf Disease Classification Using Osprey Optimization. IEEE Access.
https://doi.org/10.1109/ACCESS.2024.3358833
- Begum, S. S. A., & Syed, H. (2024). CSIU-Net+: Pepper and corn leaves classification and severity identification using hybrid optimization. Environmental Research Communications.
https://doi.org/10.1088/2515-7620/ad4900
- Begum, S. S. A., & Syed, H. (2023). Unsupervised Deep Learning for Plant Disease and Pest Identification: A Comprehensive Approach. Proceedings of the 2023 6th International Conference on Recent Trends in Advance Computing.
https://doi.org/10.1109/ICRTAC59277.2023.10480809