Banshidhar Majhi
Papers
2
Total Citations
107
H-Index
2
About
Banshidhar Majhi is a leading figure in computational intelligence and biomedical image analysis, with a particular focus on developing automated systems for pathological brain detection. His work bridges advanced machine learning, optimization algorithms, and signal processing to create efficient diagnostic tools. Among his most impactful contributions are the integration of extreme learning machines with a modified sine cosine algorithm for brain pathology detection, a study that has garnered 54 citations, and a pioneering approach combining fast discrete curvelet transform with probabilistic neural networks, cited 53 times. These papers have significantly advanced the accuracy and speed of automated brain abnormality classification, offering practical solutions for clinical decision support. Majhi’s research is characterized by its innovative fusion of nature-inspired optimization and neural architectures, setting benchmarks in the field. His work not only demonstrates high citation impact but also underscores a commitment to translating computational methods into real-world medical applications, making him a respected authority in intelligent healthcare systems.
Research Focus
Key Achievements
Top Papers
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- 2