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ORCIDMario Parente
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2020 – today
- 2023
[c30]Tejas Panambur, Mario Parente:
Improved Self-Supervised Texture Recognition of Mastcam Images by Eliminating Mixed Terrain and Range Patches. IGARSS 2023: 7292-7295- 2022
- [c29]Tejas Panambur, Deep Chakraborty, Melissa Meyer, Ralph Milliken, Erik G. Learned-Miller, Mario Parente:
Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images. CVPR Workshops 2022: 1321-1331 - [i7]Tejas Panambur, Deep Chakraborty, Melissa Meyer, Ralph Milliken, Erik G. Learned-Miller, Mario Parente:
Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images. CoRR abs/2204.09854 (2022) - 2021
- [c28]Mario Parente, Marian-Daniel Iordache:
Sparse Unmixing of Hyperspectral Data: The Legacy of SUnSAL. IGARSS 2021: 21-24 - [c27]Tejas Panambur, Mario Parente:
Improved Deep Clustering of Mastcam Images Using Metric Learning. IGARSS 2021: 2859-2862 - 2020
- [c26]Mario Parente, Tejas Panambur:
Classification of Martian Terrains via Deep Clustering of Mastcam Images. IGARSS 2020: 1054-1057 - [c25]Janice L. Bishop, Mario Parente, Arun M. Saranathan, Yuki Itoh, Catherine M. Weitz, Jessica Flahaut, Christoph Gross, Jacob M. Danielsen, Gabriela S. Usabal, Jasper K. Miura:
Implementing New Feature Extraction Techniques for Characterization of Complex Mineral Signatures of Salty Regions on Mars. IGARSS 2020: 5147-5150
2010 – 2019
- 2019
- [j10]Arun M. Saranathan
, Mario Parente:
On Clustering and Embedding Mixture Manifolds Using a Low Rank Neighborhood Approach. IEEE Trans. Geosci. Remote. Sens. 57(6): 3890-3903 (2019) - [j9]Rob Heylen, Vera Andrejchenko, Zohreh Zahiri, Mario Parente, Paul Scheunders:
Nonlinear Hyperspectral Unmixing With Graphical Models. IEEE Trans. Geosci. Remote. Sens. 57(7): 4844-4856 (2019) - [c24]Mario Parente, Yuki Itoh, Arun M. Saranathan:
New CRISM Data Products for Improved Characterization and Analysis of the Mars2020 Landing Site. IGARSS 2019: 4911-4914 - [i6]Shubhankar Deshpande, Brian D. Bue, David R. Thompson, Vijay Natraj, Mario Parente:
Learning Radiative Transfer Models for Climate Change Applications in Imaging Spectroscopy. CoRR abs/1906.03479 (2019) - 2017
- [j8]Siwei Feng, Yuki Itoh, Mario Parente, Marco F. Duarte:
Hyperspectral Band Selection From Statistical Wavelet Models. IEEE Trans. Geosci. Remote. Sens. 55(4): 2111-2123 (2017) - [j7]Rob Heylen, Mario Parente, Paul Scheunders:
Estimation of the Number of Endmembers in a Hyperspectral Image via the Hubness Phenomenon. IEEE Trans. Geosci. Remote. Sens. 55(4): 2191-2200 (2017) - [j6]Yuki Itoh, Siwei Feng, Marco F. Duarte, Mario Parente:
Semisupervised Endmember Identification in Nonlinear Spectral Mixtures via Semantic Representation. IEEE Trans. Geosci. Remote. Sens. 55(6): 3272-3286 (2017) - [j5]Yuki Itoh, Marco F. Duarte, Mario Parente:
Perfect Recovery Conditions for Non-negative Sparse Modeling. IEEE Trans. Signal Process. 65(1): 69-80 (2017) - [c23]Rob Heylen, Mario Parente, Paul Scheunders:
Estimation of the Intrinsic Dimensionality in Hyperspectral Imagery via the Hubness Phenomenon. LVA/ICA 2017: 357-366 - [c22]Rob Heylen, Mario Parente, Paul Scheunders:
Pixel purity vertex component analysis. IGARSS 2017: 213-216 - [c21]Yuki Itoh, Mario Parente:
Sparse unmixing with adaptive background. IGARSS 2017: 2593-2596 - [c20]Mario Parente, Ian Gemp, Ishan P. Durugkar:
Unmixing in the presence of nuisances with deep generative models. IGARSS 2017: 5189-5192 - [i5]Yuki Itoh, Siwei Feng, Marco F. Duarte, Mario Parente:
Semi-Supervised Endmember Identification In Nonlinear Spectral Mixtures Via Semantic Representation. CoRR abs/1701.00804 (2017) - 2016
- [j4]Arun M. Saranathan, Mario Parente:
Uniformity-Based Superpixel Segmentation of Hyperspectral Images. IEEE Trans. Geosci. Remote. Sens. 54(3): 1419-1430 (2016) - [c19]Yuki Itoh, Mario Parente:
On the performance of sparse unmixing on non-linear mixtures. IGARSS 2016: 7042-7045 - [c18]Siwei Feng, Yuki Itoh, Mario Parente, Marco F. Duarte:
Band selection from statistical wavelet models. WHISPERS 2016: 1-5 - [c17]Rob Heylen, Mario Parente, Paul Scheunders:
Estimation of the number of endmembers via the hubness phenomenon. WHISPERS 2016: 1-4 - [c16]Arun M. Saranathan, Mario Parente:
Unmixing multiple intimate mixtures via a locally low-rank representation. WHISPERS 2016: 1-4 - [i4]Siwei Feng, Yuki Itoh, Mario Parente, Marco F. Duarte:
Wavelet-Based Semantic Features for Hyperspectral Signature Discrimination. CoRR abs/1602.03903 (2016) - [i3]Ian Gemp, Ishan P. Durugkar, Mario Parente, Melinda Darby Dyar, Sridhar Mahadevan:
Deep Generative Models for Spectroscopic Analysis on Mars. CoRR abs/1608.05983 (2016) - [i2]Arun M. Saranathan, Mario Parente:
On Clustering and Embedding Manifolds using a Low Rank Neighborhood Approach. CoRR abs/1608.06669 (2016) - 2015
- [c15]Siwei Feng, Marco F. Duarte, Mario Parente:
Universality of wavelet-based non-homogeneous hidden Markov chain model features for hyperspectral signatures. CVPR Workshops 2015: 19-27 - [c14]Arun M. Saranathan, Mario Parente:
Simultaneous clustering and embedding for multiple intimate mixtures. IGARSS 2015: 2397-2400 - [c13]Yuki Itoh, Marco F. Duarte, Mario Parente:
Performance guarantees for sparse regression-based unmixing. WHISPERS 2015: 1-4 - [i1]Yuki Itoh, Marco F. Duarte, Mario Parente:
Perfect Recovery Conditions For Non-Negative Sparse Modeling. CoRR abs/1512.02743 (2015) - 2014
- [j3]Rob Heylen, Mario Parente, Paul D. Gader:
A Review of Nonlinear Hyperspectral Unmixing Methods. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(6): 1844-1868 (2014) - [c12]Siwei Feng, Yuki Itoh, Mario Parente, Marco F. Duarte:
Tailoring non-homogeneous Markov chain wavelet models for hyperspectral signature classification. ICIP 2014: 5167-5171 - [c11]Yuki Itoh, Siwei Feng, Marco F. Duarte, Mario Parente:
Hyperspectral unmixing via semantic spectral representations. MWSCAS 2014: 149-152 - [c10]Arun M. Saranathan, Mario Parente:
Unmixing multiple intimate mixtures using manifold clustering. WHISPERS 2014: 1-4 - 2013
- [c9]Marco F. Duarte, Mario Parente:
Non-homogeneous hidden Markov chain models for wavelet-based hyperspectral image processing. Allerton 2013: 154-159 - [c8]Neda Rohani, Mario Parente, Arun M. Saranathan:
Endmember detection using graph theory. IGARSS 2013: 1462-1465 - [c7]Mario Parente, Marco F. Duarte:
A new semantic wavelet-based spectral representation. WHISPERS 2013: 1-4 - [c6]Neda Rohani, Mario Parente:
Graph-based identification of boundary points for unmixing and anomaly detection. WHISPERS 2013: 1-4 - [c5]Arun M. Saranathan, Mario Parente:
Threshold based segmentation method for hyperspectral images. WHISPERS 2013: 1-4 - 2012
- [j2]José M. Bioucas-Dias, Antonio Plaza, Nicolas Dobigeon, Mario Parente, Qian Du, Paul D. Gader, Jocelyn Chanussot:
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 5(2): 354-379 (2012) - 2011
- [c4]Mario Parente, John F. Mustard, Scott L. Murchie, Frank P. Seelos:
Robust unmixing of hyperspectral images: Application to Mars. IGARSS 2011: 1291-1294 - 2010
- [j1]Mario Parente, J. Trevor Clark, Adrian J. Brown, Janice L. Bishop:
End-to-End Simulation and Analytical Model of Remote-Sensing Systems: Application to CRISM. IEEE Trans. Geosci. Remote. Sens. 48(11): 3877-3888 (2010) - [c3]Mario Parente, Antonio J. Plaza:
Survey of geometric and statistical unmixing algorithms for hyperspectral images. WHISPERS 2010: 1-4
2000 – 2009
- 2009
- [c2]Heather D. Makarewicz, Mario Parente, Janice L. Bishop:
Deconvolution of VNIR spectra using modified Gaussian modeling (MGM) with automatic parameter initialization (API) applied to CRISM. WHISPERS 2009: 1-5 - [c1]Mario Parente, J. Trevor Clark, Adrian J. Brown, Janice L. Bishop:
Simulation of the image generation process for CRISM spectrometer data. WHISPERS 2009: 1-4
Coauthor Index
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