Detailed Profile
| Name | Dr. Rajib Sarkar |
| Designation | Assistant Professor |
| Educational Qualifications | PhD |
| Experience | Teaching Experience Teaching BSc Hons & Pass Course in Computer Science in Derozio Memorial College, Rajarhat, Kolkata since 2016. Research Experience Worked as a JRF and SRF before joining the college. |
| Featured Skills | Area of Specialization Digital Signal Processing, Pattern Recognition. Area of Research Interest Fractals, Chaos and Non-linear Dynamics. |
| Accomplishments | Journals Sarkar R, Choudhury S, Dutta S, Roy A, Saha SK. Recognition of emotion in music based on deep convolutional neural network. Multimedia Tools and Applications, 2019. Sarkar R, Naskar SK, Saha SK. Raga identification from Hindustani classical music signal using compositional properties. Computing and Visualization in Science. 2017:1-12. Sarkar R, Bhaduri A, Bhaduri S, et al. Chaos Based Quantitative Risk Assessment of Cardiac Dysfunction. Chem Inform. 2016.
Conference Proceedings R Sarkar, N Biswas, S Chakraborty, “Music Genre Classification Using Frequency Domain Features”, EAIT, 2018. R Sarkar, S Dutta, A Roy, SK Saha, “Emotion Based Categorization of Music Using Low Level Features and Agglomerative Clustering”, NCVPRIPG, 2017. Sarkar R, Saha SK. Singer based classification of song dataset using vocal signature inherent in signal. In NCVPRIPG, (pp. 1-4), 2015. Sarkar R, Saha SK. Music genre classification using EMD and pitch based feature. In ICAPR, (pp. 1-6), 2015.
Book Chapter R Sarkar, A Singh, A Mondal, SK Saha, “Automatic Extraction and Identification of Bol from Tabla Signal”, ACSS 2017.
Book S Bhaduri, R Sarkar, A Bhaduri, “Chaos based on quantitative risk assessment of cardiac dysfunction”, LAP LAMBERT Academic Publishing (May 19, 2017), ISBN 978-3330319868 |