Birendra Kumar Verma

ORCID: 0000-0003-3277-4687
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About
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Research Areas
  • Software Engineering Research
  • Information and Cyber Security
  • Software Reliability and Analysis Research
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Radiomics and Machine Learning in Medical Imaging
  • Air Quality and Health Impacts
  • Advanced Malware Detection Techniques
  • Structural Health Monitoring Techniques
  • Air Quality Monitoring and Forecasting
  • Infrastructure Maintenance and Monitoring
  • Vehicle emissions and performance
  • Advanced Data Processing Techniques

Banasthali University
2023-2024

Central Queensland University
2006

Abstract Pneumonia is a widespread and acute respiratory infection that impacts people of all ages. Early detection treatment pneumonia are essential for avoiding complications enhancing clinical results. We can reduce mortality, improve healthcare efficiency, contribute to the global battle against disease has plagued humanity centuries by devising deploying effective methods. Detecting not only medical necessity but also humanitarian imperative technological frontier. Chest X-rays...

10.1038/s41598-024-52703-2 article EN cc-by Scientific Reports 2024-01-30

Abstract Worldwide, pneumonia is the leading cause of infant mortality. Experienced radiologists use chest X-rays to diagnose and other respiratory diseases. The diagnostic procedure's complexity causes disagree with decision. Early diagnosis only feasible strategy for mitigating disease's impact on patent. Computer-aided diagnostics improve accuracy diagnosis. Recent studies established that Quaternion neural networks classify predict better than real-valued networks, especially when...

10.1038/s41598-023-35922-x article EN cc-by Scientific Reports 2023-06-03

This paper presents a neural network based technique for the classification of segments road images into cracks and normal images. The density histogram features are extracted. passed to with without cracks. Once classified non-cracks, they another crack type after segmentation. Some experiments were conducted promising results obtained. selected comparative analysis included in this paper.

10.1109/ijcnn.2006.1716193 article EN The 2006 IEEE International Joint Conference on Neural Network Proceedings 2006-10-30
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