D. S. Bormane

发表

Simulation of improved CMOS digital pixel sensor for computer vision

Arvind D. Shaligram, Y. V. Chavan, D. K. Mishra, 2017 .

Automatic Emotion Recognition through Handwriting Analysis: A Review

D. S. Bormane, S. V. Kedar, Aaditi Dhadwal, 2015, 2015 International Conference on Computing Communication Control and Automation.

BER performance of OFDM system with adaptive modulation

D. S. Bormane, Nita J. Borkar, 2012, 2012 IEEE International Conference on Complex Systems (ICCS).

Musical instrument classification using higher order spectra

D. S. Bormane, D. G. Bhalke, C. B. Rama Rao, 2014, 2014 International Conference on Signal Processing and Integrated Networks (SPIN).

Stringed musical instrument recognition using fractional fourier transform and linear discriminant analysis

D. S. Bormane, D. G. Bhalke, C. B. Rama Rao, 2014, 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT).

A Novel Techniques for Classification of Musical Instruments

D. S. Bormane, Meenakshi Dusane, 2013 .

High Performance EEG Analysis for Brain Interface

D. S. Bormane, D. T. Ingole, Alka Mahajan, 2009 .

Hybridization of Fractional Fourier Transform and Acoustic Features for Musical Instrument Recognition

D. S. Bormane, D. G. Bhalke, C. B. Rama Rao, 2014 .

Dynamic time warping technique for musical instrument recognition for isolated notes

D. S. Bormane, C. B. Rama Rao, D. G. Bhalke, 2011, 2011 International Conference on Emerging Trends in Electrical and Computer Technology.

Comparison of different CBIR techniques

D. S. Bormane, Sonali Bhadoria, C. G. Dethe, 2011, 2011 3rd International Conference on Electronics Computer Technology.

Performance Comparison of K-NN, Minimum Distance and SVM Classifiers Used to Predict Hypertension Based on Manuscript

D. S. Bormane, Shailaja C. Patil, Seema V. Kedar, 2017 .

Hybridisation of Mel Frequency Cepstral Coefficient and Higher Order Spectral Features for Musical Instruments Classification

D. S. Bormane, C. B. Rama Rao, D. G. Bhalke, 2016 .

Analysis of nonlinear and non-stationary signal to extract the features using Hilbert Huang transform

D. S. Bormane, A. N. Paithane, A. Paithane, 2014, 2014 IEEE International Conference on Computational Intelligence and Computing Research.

Electrocardiogram signal analysis using empirical mode decomposition and Hilbert spectrum

D. S. Bormane, A. N. Paithane, A. Paithane, 2015, 2015 International Conference on Pervasive Computing (ICPC).

Electroencephalograph Signal Analysis During Bramari

S. T. Patil, D. S. Bormane, D. Bormane, 2006, 9th International Conference on Information Technology (ICIT'06).