113 citations · 328 across the 16 of their papers we have counts for
10 papers · 1 filter
Spatiotemporally adaptive compression for scientific dataset with feature preservation -- a case study on simulation data with extreme climate events analysis
Qian Gong, Chengzhu Zhang, Xin Liang +10
Scientific discoveries are increasingly constrained by limited storage space and I/O capacities. For time-series simulations and experiments, their data often need to be decimated…
Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video
Xiaohui Huang, Pan He, Anand Rangarajan +1
In Intelligent Transportation System, real-time systems that monitor and analyze road users become increasingly critical as we march toward the smart city era. Vision-based framewo…
Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification
Chengliang Yang, Anand Rangarajan, Sanjay Ranka
We develop three efficient approaches for generating visual explanations from 3D convolutional neural networks (3D-CNNs) for Alzheimer's disease classification. One approach conduc…
A Gaussian mixture model representation of endmember variability in hyperspectral unmixing
Yuan Zhou, Anand Rangarajan, Paul D. Gader
Hyperspectral unmixing while considering endmember variability is usually performed by the normal compositional model (NCM), where the endmembers for each pixel are assumed to be s…
Disaggregation of SMAP L3 Brightness Temperatures to 9km using Kernel Machines
Subit Chakrabarti, Tara Bongiovanni, Jasmeet Judge +2
In this study, a machine learning algorithm is used for disaggregation of SMAP brightness temperatures (T) from 36km to 9km. It uses image segmentation to cluster th…
A Grassmannian Graph Approach to Affine Invariant Feature Matching
Mark Moyou, John Corring, Adrian Peter +1
In this work, we present a novel and practical approach to address one of the longstanding problems in computer vision: 2D and 3D affine invariant feature matching. Our Grassmannia…
Spatial Scaling of Satellite Soil Moisture using Temporal Correlations and Ensemble Learning
Subit Chakrabarti, Jasmeet Judge, Tara Bongiovanni +2
A novel algorithm is developed to downscale soil moisture (SM), obtained at satellite scales of 10-40 km by utilizing its temporal correlations to historical auxiliary data at fine…
A spatial compositional model (SCM) for linear unmixing and endmember uncertainty estimation
Yuan Zhou, Anand Rangarajan, Paul Gader
The normal compositional model (NCM) has been extensively used in hyperspectral unmixing. However, most of the previous research has focused on estimation of endmembers and/or thei…
Downscaling Microwave Brightness Temperatures Using Self Regularized Regressive Models
Subit Chakrabarti, Jasmeet Judge, Anand Rangarajan +1
A novel algorithm is proposed to downscale microwave brightness temperatures (), at scales of 10-40 km such as those from the Soil Moisture Active Passive mission to…
A new variational principle for the Euclidean distance function: Linear approach to the non-linear eikonal problem
Karthik S. Gurumoorthy, Anand Rangarajan
We present a fast convolution-based technique for computing an approximate, signed Euclidean distance function on a set of 2D and 3D grid locations. Instead of solving the non-…