VEERA BABU A

@cmrcet.ac.in

Assistant Professor, Department of Electronics & Communication Engineering
cmr college of engineering & technology

VEERA BABU A


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RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials
2

Scopus Publications

Scopus Publications

  • A Unique Method Using Deep Learning to Detect Brain Tumors and Performance Enhancement
    Jonnadula Narasimharao, Suraya Mubeen, V. Santosh Kumar, Maisa Soujanya, M. Nagaraju Naik, A. Veerababu
    Lecture Notes in Networks and Systems, 2025
  • Insistence ML Based Exemplification in Case of VR: An Intensive Review
    A. Veerababu, Deepak Kumar, Laith H. Alzubaidi, Archana Saxena, Saloni Bansal, Yabesh Abraham Durairaj Isravel
    2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2024, 2024
    Although augmented reality (AR) is not a novel concept, there has been a surge in popular interest in it recently. It has the ability to improve audio, add comments and contextual facts, and overlay graphics to make our surroundings more interesting. Applications for AR are numerous and include gaming, education, healthcare, industrial maintenance, TV and film production, and entertainment. This work offers a refined technique for image-based augmented reality, concentrating on two significant aspects of the augmented reality process. First, in order to increase precision and effectiveness, we include machine learning into the detecting stage. Second, in order to enhance the registration of improved pictures, we use probabilistic presentation algorithms and covariance matrix of dense picture descriptors. Our goal is to get dependable and instantaneous picture enhancement by painstaking approach and algorithm optimisation. We offer a thorough justification of our technique selection procedure and contrast our strategy with other accepted practices in the industry. Lastly, we carry out an assessment of the suggested method together with a performance analysis customised for a particular use case.