Publicatons

1.   A. Kandaswamy, E. Malar, T. D. Ahilaa and R. Indrani, "Adaptive algorithms for detection of microcalcification in mammograms with the aid of Graphical programming language, a CAD system," 2010 Second International conference on Computing, Communication and Networking Technologies, Karur, India, 2010, pp. 1-5, doi: 10.1109/ICCCNT.2010.5591598.

2.   Malar, E., Gauthaam, M., & Chakravarthy, D. (2011). A novel approach for the detection of drunken driving using the power spectral density analysis of EEG. Int. J. Comput. Appl, 0975-  8887.

3.   Malar, E., Kandaswamy, A., Chakravarthy, D., & Dharan, A. G. (2012). A novel approach for detection and classification of mammographic microcalcifications using wavelet analysis and extreme learning machine. Computers in biology and medicine, 42(9),898-905

4.   Malar, E., Kandaswamy, A., Kirthana, S. S., & Nivedhitha, D. (2012, December). A comparative study on mammographic image denoising technique using wavelet, curvelet and contourlet transforms. In Machine Vision and Image Processing (MVIP), 2012 International Conference on (pp. 65-68).IEEE.

5.   Malar, E., Gauthaam, M., Kalaikamal, M., & Muthukrishnan, S. (2012). The EEG based driver safety system. International Journal of Engineering and Technology, 4(3), 340.

6.   Malar, E., Kandaswamy, A., & Gauthaam, M. (2013, December), Multiscale and multilevel  wavelet analysis of mammogram using complex neural network. In International Conference on Swarm, Evolutionary, and Memetic Computing (pp. 658-668). Springer,Cham.

7.   Malar, E., Ramasamy, S., & Arumugam, K. (2014, April). A novel method for benign and malignant characterization of mammographic microcalcifications employing waveatom  features and circular complex valued—Extreme Learning Machine. In  Intelligent  Sensors,  Sensor Networks and Information Processing (ISSNIP), 2014 IEEE  Ninth International Conference on  (pp. 1-6).IEEE.

8.   Malar, E., Gauthaam, M., Kalaikamal, M., & Muthukrishnan, S. (2012), The EEG Based Driver Safety System. International Journal of Engineering and Technology, 4(3),340.

9.   Kandaswamy, A., Malar, E., Ahilaa, T. D., &Indrani, R. (2010, July), Adaptive algorithms for detection of microcalcification in mammograms with the aid of Graphical programming language,   a CAD system. In Computing Communication and Networking Technologies (ICCCNT), 2010 International Conference on (pp. 1-5).IEEE.

10.       Elangeeran, M., Ramasamy, S., & Arumugam, K. (2014, April). A novel method for benign and malignant characterization of mammographic microcalcifications employing waveatom features and circular complex valued—extreme learning machine. In 2014 IEEE ninth international conference on intelligent sensors, sensor networks and information processing (ISSNIP) (pp. 1-6). IEEE.

11.  E. Malar, Priya K and A. Kandaswamy.(2015,Auguest), Comparative study of curvelet and waveatom transform in the classification of microcalcifications using complex neural networks. International Journal of Applied Engineering Research,10(13),32992-32999

12.  M Jothibasu, M Karthik, E. Malar, S Boopathy, M Senthil Kumar (2018), Improved Reversible Data Hiding Through Image Using Different Hiding and Compression Techniques, International Journal of Innovative Technology and Exploring Engineering,Volume-8, Issue-2S2, pp 327 – 330

13.  Dr. E. Malar, Raghu Prasath V, Rahavi S, (2020), Prediction of Cardio Vascular Disease from Retinal Fundus Images Using Neural Networks, Sixth International conference of Electrical energy System, Feb 2020.

14.  Malar, E., and M. Gauthaam. "Wavelet analysis of EEG for the identification of alcoholics using probabilistic classifiers and neural networks." International Journal of Intelligence and Sustainable Computing 1.1 (2020): 3-18.

15.  Dr. E. Malar, Raghu Prasath V, Rahavi S. (2020). Prediction Of CVD From Retinal Fundus Images Using CNN. International Journal of Advanced Science and Technology, 29(9s), 3551 - 3559.

16.  Jeyakumar, P., Malar, E., Niveda, S. et al. Optimal Microwave Wireless Backhaul Link Design Using a Massive MIMO for 5G HetNet-Practical Deployment Scenario. Wireless Pers Commun 120, 2117–2133 (2021). https://doi.org/10.1007/s11277-021-08543-8

17.  Jeyakumar, P., Malar, E., Idnani, N. et al. Large Antenna Array with Hybrid Beamforming System for 5G Outdoor Mobile Broadband Communication Deployments. Wireless Pers Commun 120, 2001–2027 (2021). https://doi.org/10.1007/s11277-021-08457-5

18.  Malar Elangeeran, and P. Deepan Chakravarthi. "Extreme learning machine-based investigation on automated detection of architectural distortion in mammograms." International Journal of Operational Research 41.4 (2021): 477-491.

19.  Kandaswamy, A., Malar, E., Ahilaa, T. D., & Indrani, R. (2021). Detection of dichromacy and achromatopsia using LabVIEW. International Journal of Medical Engineering and Informatics, 13(4), 334-345.

20.   Jeyakumar, P., Malar, E., Srinitha, S. et al. Hybrid Beamforming in Large-scale Antenna Array for 5G Indoor Communication Network Deployments. Wireless Pers Commun 126, 2513–2532 (2022).

21.   Sowmiya, M., Rekha, B. B., Malar, E., & Kumaran, K. A. (2022). Hierarchical learning model for early prediction of coronary artery atherosclerosis. International Journal of Operational Research, 44(4), 473-495.

22.  Jeyakumar, P, Dr E Malar, et al. (2022) "Beamforming design with fully connected analog beamformer using deep learning." INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS.

23.       Marappan, J., Murugesan, K., Elangeeran, M., & Subramanian, U. (2023). Human retinal biometric recognition system based on multiple feature extraction. Journal of Electronic Imaging, 32(1), 013008.