Sheilla Ann Pacheco | Machine Learning for Computer Vision | Editorial Board Member

Assist. Prof. Dr. Sheilla Ann Pacheco | Machine Learning for Computer Vision | Editorial Board Member

Faculty | North Eastern Mindanao State University | Philippines

Sheilla Ann B. Pacheco is an Assistant Professor II of Computer Science at North Eastern Mindanao State University, Philippines. Her research focuses on image processing, machine learning, computer vision, and AI-driven healthcare applications. She has authored multiple peer-reviewed journal and conference publications, with works appearing in international venues such as Procedia Computer Science, International Journal of Computers and Applications, and IEEE conferences. Her studies address content-based image retrieval, facial biometrics, adversarial attacks, and ensemble learning for disease prediction. Through interdisciplinary collaborations, her research contributes to advancing robust AI systems with practical societal impact in healthcare, education, and security domains.

 

Citation Metrics (Scopus)

30

20

10

5

0

Citations
9

Documents
8

h-index
2

🟦 Citations 🟥 Documents 🟩 h-index

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Featured Publications


Enhanced content-based image retrieval using multivisual features fusion.

– International Journal of Computers and Applications. (2025). Cited By : 4

Robust face recognition under adversarial attack using SARGAN model and improved cross triple MobileNetV1.

– In K. Arai (Ed.), Advances in Information and Communication: Proceedings of the Future of Information and Communication Conference (pp. 491–510). Springer. (2025). Cited By: 2

A comprehensive survey on federated learning and its applications in health care.

– In Proceedings of the 2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) (pp. 407–412). IEEE.. (2024). Cited By: 1

Simy Baby | Applications of Computer Vision | Best Researcher Award

Mrs. Simy Baby | Applications of Computer Vision | Best Researcher Award

Researcher | National Institute of Technology | India

Mrs. Simy Baby is a pioneering researcher at the National Institute of Technology, Tiruchirappalli, with extensive expertise in machine learning, semantic communication, computer vision, and mmWave radar signal processing. Her research bridges the gap between radar sensing and intelligent communication frameworks, focusing on efficient feature extraction, complex-valued encoding, and task-oriented inference.Her seminal work, “Complex Chromatic Imaging for Enhanced Radar Face Recognition” (Computers and Electrical Engineering,  introduced a novel representation that preserves amplitude and phase information of mmWave radar signals, achieving an exceptional recognition accuracy. Another significant contribution, “Complex-Valued Linear Discriminant Analysis on mmWave Radar Face Signatures for Task-Oriented Semantic Communication” (IEEE Transactions on Cognitive Communications and Networking ), proposed a CLDA-based encoding framework enhancing feature interpretability and robustness under channel variations. Current investigations include Data Fusion Discriminant Analysis (DFDA) for multi-view activity recognition and Semantic Gaussian Process Regression (GPR) for vehicular pose estimation, highlighting her commitment to multitask semantic communication systems.Dr. Baby has 21 publications with 20 citations and an h-index of 3.  demonstrating a rapidly growing impact in her field. She is an active member of the Indian Society for Technical Education (ISTE) and contributes to the scientific community through innovative research that combines theory and practical applications. Her work on radar-based recognition, semantic feature transmission, and multi-task inference frameworks holds significant potential for intelligent transportation systems, human activity recognition, and bandwidth-efficient communication technologies.Through her research, Dr. Baby has established herself as a leading figure in advancing radar imaging and semantic communication, providing scalable solutions that merge high-performance computing with real-world societal applications. Her vision continues to shape the future of intelligent sensing and communication systems globally.

Profiles: Google Scholar | ORCID | Scopus 

Featured Publications

1. Ansal, K. A., Rajan, C. S., Ragamalika, C. S., & Baby, S. M. (2022). A CPW fed monopole antenna for UWB/Ku band applications. Materials Today: Proceedings, 51, 585–590. Cited By : 5

2. Ansal, K. A., Ragamalika, C. S., Rajan, C. S., & Baby, S. M. (2022). A novel ACS fed antenna with comb shaped radiating strip for triple band applications. Materials Today: Proceedings, 51, 332–338. Cited By : 4

3. Ansal, K. A., Kumar, A. S., & Baby, S. M. (2021). Comparative analysis of CPW fed antenna with different substrate material with varying thickness. Materials Today: Proceedings, 37, 257–264. Cited By : 4

4. Baby, S. M., & Gopi, E. S. (2025). Complex chromatic imaging for enhanced radar face recognition. Computers and Electrical Engineering, 123, 110198. Cited By : 3

5.Ansal, K. A., Shanmuganatham, T., Baby, S. M., & Joy, A. (2015). Slot coupled microstrip antenna for C and X band application. International Journal of Advanced Research Trends in Engineering and Technology.Cited By : 3

Dr. Simy M. Baby’s research advances the integration of semantic communication and computer vision, enabling high-accuracy radar-based recognition and task-oriented inference. Her work has significant implications for intelligent transportation, human activity monitoring, and bandwidth-efficient communication, driving innovation in both science and industry globally.