Amarjit Roy
Ghani Khan Choudhury Institute of Engineering and Technology, VIT-AP Campus, National Institute Of Technology Silchar, National Institute of Technology, Silchar, BML Munjal University
About
Dr. Amarjit Roy received the M. Tech degree from NIT Silchar in 2014, and the Ph.D. degree from NIT Silchar in Electronics and Communication Engineering. After that, he joined as an Assistant Professor in BML Munjal University in 2017. In July 2020, he joined as an Assistant Professor Sr. Grade 1 in VIT AP University. Now, he is working as an Assistant Professor at Ghani Khan Choudhury Institute of Engineering and Technology, Malda (A CFTI under MoE). His research interests include Image noise removal, soft computing, biomedical image processing etc. He has published many papers in journals such as IEEE, Elsevier, Springer etc.
Employment
-
Ghani Khan Choudhury Institute of Engineering and Technology Assistant Professor2021 - Present
-
VIT-AP Campus Assistant Professor2020 - 2021
-
BML Munjal University Assistant Professor2017 - 2020
Education
-
National Institute Of Technology Silchar PhD2014 - 2017
-
National Institute of Technology, Silchar MTech2012 - 2014
Projects & Funding
Projects & funding information is unavailable.
Publications (20)
- Improved Switching Vector Median Filter for Removal of Impulse Noise from Color Images Save
- Benign–Malignant Mass Characterization Based on Multi-gradient Quinary Patterns Save
- Removal of ‘Salt & Pepper’ noise from color images using adaptive fuzzy technique based on histogram estimation Save
- SVM-based robust image watermarking technique in LWT domain using different sub-bands Save
- Fuzzy SVM based fuzzy adaptive filter for denoising impulse noise from color images Save
- Removal of Impulse Noise from Gray Images Using Fuzzy SVM Based Histogram Fuzzy Filter Save
- Region Adaptive Fuzzy Filter: An Approach for Removal of Random-Valued Impulse Noise Save
- Neural network based robust image watermarking technique in LWT domain Save
- Malaria infected erythrocyte classification based on a hybrid classifier using microscopic images of thin blood smear Save
- Erratum to: Malaria infected erythrocyte classification based on a hybrid classifier using microscopic images of thin blood smear (Multimedia Tools and Applications, (2018), 77, 1, (631-660), 10.1007/s11042-016-4264-7) Save