53 citations · 82 across the 4 of their papers we have counts for
6 papers
Reconstructing Cardiac Electrical Excitations from Optical Mapping Recordings
Christopher D. Marcotte, Matthew J. Hoffman, Flavio H. Fenton +1
The reconstruction of electrical excitation patterns through the unobserved depth of the tissue is essential to realizing the potential of computational models in cardiac medicine.…
Calibrated Vehicle Paint Signatures for Simulating Hyperspectral Imagery
Zachary Mulhollan, Aneesh Rangnekar, Timothy Bauch +2
We investigate a procedure for rapidly adding calibrated vehicle visible-near infrared (VNIR) paint signatures to an existing hyperspectral simulator - The Digital Imaging and Remo…
AeroRIT: A New Scene for Hyperspectral Image Analysis
Aneesh Rangnekar, Nilay Mokashi, Emmett Ientilucci +2
We investigate applying convolutional neural network (CNN) architecture to facilitate aerial hyperspectral scene understanding and present a new hyperspectral dataset-AeroRIT-that…
Aerial Spectral Super-Resolution using Conditional Adversarial Networks
Aneesh Rangnekar, Nilay Mokashi, Emmett Ientilucci +2
Inferring spectral signatures from ground based natural images has acquired a lot of interest in applied deep learning. In contrast to the spectra of ground based images, aerial sp…
Tracking in Aerial Hyperspectral Videos using Deep Kernelized Correlation Filters
Burak Uzkent, Aneesh Rangnekar, Matthew J. Hoffman
Hyperspectral imaging holds enormous potential to improve the state-of-the-art in aerial vehicle tracking with low spatial and temporal resolutions. Recently, adaptive multi-modal…
Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps
Burak Uzkent, Aneesh Rangnekar, M. J. Hoffman
Hyperspectral cameras can provide unique spectral signatures for consistently distinguishing materials that can be used to solve surveillance tasks. In this paper, we propose a nov…