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Assistant Professor

sushree.behera@iiitb.ac.in

Education : Ph.D. (IIT Bhubaneswar)

Dr. Sushree S. Behera received her Doctoral degree from the School of Electrical Sciences, Indian Institute of Technology Bhubaneswar where she worked in the area of Biometrics and Computer Vision using Deep Learning. Prior to that she completed her MTech from the Department of Electrical Engineering, Indian Institute of Technology Indore. Before joining IIIT Bangalore, she worked as a Post- Doctoral Research Fellow at Jio Institute, Navi Mumbai, India, from April 2023 to November 2023. Her research interests lie in the fields of Biometrics, Computer Vision, Medical Image Analysis, Deep Learning, and Machine Learning.

Computer Vision, Machine Learning, Image Processing, Signal Processing, Medical Image Analysis, Natural Language Processing

Journal Articles:

1.Sushree S. Behera and Niladri B. Puhan, “Dual-spectrum Network: Exploring Deep Visual Feature to Attribute Mapping for Cross-spectral Periocular Recognition,” Journal of Electronic Imaging, vol. 32, no. 3, pp. 033031–0330331, June 2023. DOI: https://doi.org/10.1117/1.JEI.32.3.033031

2.Niladri B. Puhan and Sushree S. Behera, “Holistic Feature Reconstruction-based 3-D Attention Mechanism for Cross-spectral Periocular Recognition,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 435–448, Nov. 2022. DOI:10.1109/TIFS.2022.3224854

3.Sushree S. Behera and Niladri B. Puhan, “High boost 3-D Attention Network for Cross-spectral Periocular Recognition,” IEEE Sensors Letters, vol. 6, no. 9, pp. 1–4, Sept. 2022. DOI: 10.1109/LSENS.2022.3204710

4.Sushree S. Behera, Niladri B. Puhan, and Sapna S. Mishra, “Perturbed Attention-Assisted Siamese Network for Cross-spectral Periocular Recognition,” IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 4, no. 2, pp. 210–221, April 2022. DOI:10.1109/TBIOM.2022.3174620

5.Sushree S. Behera, Sapna S. Mishra, Bappaditya Mandal, and Niladri B. Puhan, “Variance-guided Attention-based Twin Deep Network for Cross-spectral Periocular Recognition,” Image and Vision Computing, vol. 104, no. 104016, Sept. 2020. DOI: https://doi.org/10.1016/j.imavis.2020.104016

Conferences:

1.Sushree S. Behera, Bappaditya Mandal, and Niladri B. Puhan, “Twin deep convolutional neural network-based cross-spectral periocular recognition,” In IEEE National Conference on Communication (NCC), pages 1–6, 2020. DOI:10.1109/NCC48643.2020.9056008

2.Sushree S. Behera, Bappaditya Mandal, and Niladri B. Puhan, “Cross-spectral periocular recognition: A survey,” in Lecture Notes in Electrical Engineering, vol. 545, Springer, Singapore, 2019, pp. 731–741. DOI: 10.1007/978-981-13-5802-9_64

3.Sushree S. Behera, Mahesh Gour, Vivek Kanhangad, and Niladri Puhan. “Periocular recognition in cross-spectral scenario,” In IEEE International Joint Conference on Biometrics (IJCB), pp. 681–687, 2017. DOI: 10.1109/BTAS.2017.8272757

 

 

NC 854: Digital Image Processing (Jan 2024 - Present)