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cs.CV2017
Learning Invariant Riemannian Geometric Representations Using Deep Nets
Suhas Lohit, Pavan Turaga
Non-Euclidean constraints are inherent in many kinds of data in computer vision and machine learning, typically as a result of specific invariance requirements that need to be resp…
cs.CV2017
Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images
Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche +2
Traditional algorithms for compressive sensing recovery are computationally expensive and are ineffective at low measurement rates. In this work, we propose a data driven non-itera…