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Sukadev Meher
Also published under:S. Meher
Affiliation
Department of Electronics and Communication Engineering, National Institute of Technology Rourkela, Rourkela, India
Topic
Convolutional Neural Network,Acute Myeloid Leukemia,Computational Efficiency,Deep Learning,F1 Score,Acute Leukemia,Convolutional Layers,High-resolution Images,Image Grid,Image Resampling,Leukocytes,Low-resolution Images,Order Derivative,Sickle Cell Disease,Transfer Learning,Very High Frequency,Bicubic,Blood Cells,Classification Performance,Deblurring,Deep Convolutional Neural Network,Deep Learning Strategies,Deep Semantic Segmentation,Dice Similarity Coefficient,Edge Details,Edge Enhancement,Efficient Classification,Excellent Performance,Hematological Diseases,High Order,Intersection Over Union,Leukemia Detection,Low-pass,Machine Learning,Presence Of Edges,Presence Of Noise,Quantitative Performance,Residual Learning,Segmentation Accuracy,Segmentation Performance,Semantic Segmentation,Skip Connections,Structural Similarity Index Measure,Support Vector Machine,2nd Order,4th Order,Active Contour Model,Acute Lymphoblastic Leukemia,Acute Lymphoblastic Leukemia Classification,Acute Model,
Biography
Sukadev Meher (Member, IEEE) received the B.Sc. (Engg.) degree in electronics and communication engineering from the University College of Engineering (UCE), Burla, India, in 1984, the M.E. degree in electronics systems and communication engineering from the Regional Engineering College, Rourkela, India, in 1992, and the Ph.D. degree in electronics engineering and image processing from the National Institute of Technology Rourkela (NIT Rourkela), in 2005. He is currently a Professor with the Department of Electronics and Communication Engineering, NIT Rourkela. He has been assuming this position, since July 2011. He has over 100 papers in international/national journals and conferences. His Google Scholar H-index is 17 with more than 1300 citations. His research interests include image processing, signal processing, medical image processing, deep learning, and machine learning.