Nilesh Kulkarni

Employment

• Smt Kashibai Navale College of Engineering Vadgaon Lecturer
  2017 - Present
• All India Shri Shivaji Memorial Society's Institute of Information Technology Visiting Faculty
  2016 - Present

Education

• All India Shri Shivaji Memorial Society's Institute of Information Technology Master of Engineering in Electronics & Telecommunication
  2013 - 2015
• G H Raisoni Institute of Engineering & Technology Bachelor of Engineering
  2009 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (17)

• Convolutional neural network-based diagnosis of alzheimer’s disease using time–frequency features
  Lecture Notes in Networks and Systems 2020 DOI: 10.1007/978-981-15-3338-9_38
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• ROI based Lossless Medical Image Compression using Integer Wavelet Transform and Run-length Coding
  International Journal of Future Generation Communication and Networking 2020
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• Role of Different Features in Diagnosis of Alzheimer Disease
  EEG-Based Diagnosis of Alzheimer Disease 2018 DOI: 10.1016/b978-0-12-815392-5.00003-4
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• Use of Complexity Features for Diagnosis of Alzheimer Disease
  EEG-Based Diagnosis of Alzheimer Disease 2018 DOI: 10.1016/b978-0-12-815392-5.00004-6
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• Results, Discussions, and Research Challenges
  EEG-Based Diagnosis of Alzheimer Disease 2018 DOI: 10.1016/b978-0-12-815392-5.00006-x
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• Introduction
  EEG-Based Diagnosis of Alzheimer Disease 2018 DOI: 10.1016/b978-0-12-815392-5.00001-0
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• Electroencephalogram and Its Use in Clinical Neuroscience
  EEG-Based Diagnosis of Alzheimer Disease 2018 DOI: 10.1016/b978-0-12-815392-5.00002-2
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• Classification Algorithms in Diagnosis of Alzheimer’s Disease
  EEG-Based Diagnosis of Alzheimer Disease 2018 DOI: 10.1016/b978-0-12-815392-5.00005-8
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• Acknowledgments
  EEG-Based Diagnosis of Alzheimer Disease 2018 DOI: 10.1016/b978-0-12-815392-5.00012-5
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• EEG Signal Analysis for Mild Alzheimer’s Disease Diagnosis by Means of Spectral- and Complexity-Based Features and Machine Learning Techniques
  Proceedings of the 2nd International Conference on Data Engineering and Communication Technology 2018 DOI: 10.1007/978-981-13-1610-4_40
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