B
B. Uma Shankar
Researcher at Indian Statistical Institute
Publications - 57
Citations - 3039
B. Uma Shankar is an academic researcher from Indian Statistical Institute. The author has contributed to research in topics: Image segmentation & Segmentation. The author has an hindex of 18, co-authored 50 publications receiving 2337 citations.
Papers
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Book ChapterDOI
ROI Segmentation from Brain MR Images with a Fast Multilevel Thresholding
TL;DR: A novel region of interest (ROI) segmentation for detection of Glioblastoma multiforme (GBM) tumor in magnetic resonance (MR) images of the brain is proposed using a two-stage thresholding method using a novel meta-heuristic optimization technique called Discrete Curve Evolution.
Proceedings ArticleDOI
A novel multilabel classification of remote sensing images using XGBoost
TL;DR: The problem of classifying a satellite image-chip, into one class or multiple classes, is explored using multilabel classification framework and gives F1-score of 0.87411, which is far better than state-of-the-art methods, like Random Forest and Gaussian Naive Bayes.
Book ChapterDOI
Unsupervised Change Detection in Remote Sensing Images Using CNN Based Transfer Learning
TL;DR: In this paper, three CNN models, VGG19, InceptionV3 and ResNet50, were used for feature extraction using transfer learning, followed by KMeans and Fuzzy C-Means(FCM) clustering algorithms for generating change maps.
Journal ArticleDOI
DeepSGP: Deep Learning for Gene Selection and Survival Group Prediction in Glioblastoma
Ritaban Kirtania,Subhashis Banerjee,Sayantan Laha,B. Uma Shankar,Raghunath Chatterjee,Sushmita Mitra +5 more
TL;DR: A new Autoencoder (AE)-based strategy for the prediction of survival (low or high) of GBM patients, using the RNA-seq data of 129 GBM samples from The Cancer Genome Atlas (TCGA), which is a novel interdisciplinary approach to integrating genomics with deep learning towards survival prediction.