Deconvolution of VNIR spectra using modified Gaussian modeling (MGM) with automatic parameter initialization (API) applied to CRISM. - Heather D. Makarewicz; Mario Parente; Janice L. Bishop (WHISPERS, 2009)

Simulation of the image generation process for CRISM spectrometer data. - Mario Parente; J. Trevor Clark; Adrian J. Brown; Janice L. Bishop (WHISPERS, 2009)

Survey of geometric and statistical unmixing algorithms for hyperspectral images. - Mario Parente; Antonio J. Plaza (WHISPERS, 2010)

End-to-End Simulation and Analytical Model of Remote-Sensing Systems: Application to CRISM. - Mario Parente; J. Trevor Clark; Adrian J. Brown; Janice L. Bishop (IEEE Trans. Geosci. Remote. Sens., 2010)

Robust unmixing of hyperspectral images: Application to Mars. - Mario Parente; John F. Mustard; Scott L. Murchie; Frank P. Seelos (IGARSS, 2011)

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches. - José M. Bioucas-Dias; Antonio Plaza; Nicolas Dobigeon; Mario Parente; Qian Du 001; Paul D. Gader; Jocelyn Chanussot (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2012)

Non-homogeneous hidden Markov chain models for wavelet-based hyperspectral image processing. - Marco F. Duarte; Mario Parente (Allerton, 2013)

Endmember detection using graph theory. - Neda Rohani; Mario Parente; Arun M. Saranathan (IGARSS, 2013)

A new semantic wavelet-based spectral representation. - Mario Parente; Marco F. Duarte (WHISPERS, 2013)

Graph-based identification of boundary points for unmixing and anomaly detection. - Neda Rohani; Mario Parente (WHISPERS, 2013)

Threshold based segmentation method for hyperspectral images. - Arun M. Saranathan; Mario Parente (WHISPERS, 2013)

Tailoring non-homogeneous Markov chain wavelet models for hyperspectral signature classification. - Siwei Feng; Yuki Itoh; Mario Parente; Marco F. Duarte (ICIP, 2014)

Hyperspectral unmixing via semantic spectral representations. - Yuki Itoh; Siwei Feng; Marco F. Duarte; Mario Parente (MWSCAS, 2014)

Unmixing multiple intimate mixtures using manifold clustering. - Arun M. Saranathan; Mario Parente (WHISPERS, 2014)

A Review of Nonlinear Hyperspectral Unmixing Methods. - Rob Heylen; Mario Parente; Paul D. Gader (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Universality of wavelet-based non-homogeneous hidden Markov chain model features for hyperspectral signatures. - Siwei Feng; Marco F. Duarte; Mario Parente (CVPR Workshops, 2015)

Simultaneous clustering and embedding for multiple intimate mixtures. - Arun M. Saranathan; Mario Parente (IGARSS, 2015)

Performance guarantees for sparse regression-based unmixing. - Yuki Itoh; Marco F. Duarte; Mario Parente (WHISPERS, 2015)

On the performance of sparse unmixing on non-linear mixtures. - Yuki Itoh; Mario Parente (IGARSS, 2016)

Band selection from statistical wavelet models. - Siwei Feng; Yuki Itoh; Mario Parente; Marco F. Duarte (WHISPERS, 2016)

Estimation of the number of endmembers via the hubness phenomenon. - Rob Heylen; Mario Parente; Paul Scheunders (WHISPERS, 2016)

Unmixing multiple intimate mixtures via a locally low-rank representation. - Arun M. Saranathan; Mario Parente (WHISPERS, 2016)

Wavelet-Based Semantic Features for Hyperspectral Signature Discrimination. - Siwei Feng; Yuki Itoh; Mario Parente; Marco F. Duarte (CoRR, 2016)

Deep Generative Models for Spectroscopic Analysis on Mars. - Ian Gemp; Ishan P. Durugkar; Mario Parente; Melinda Darby Dyar; Sridhar Mahadevan (CoRR, 2016)

On Clustering and Embedding Manifolds using a Low Rank Neighborhood Approach. - Arun M. Saranathan; Mario Parente (CoRR, 2016)

Uniformity-Based Superpixel Segmentation of Hyperspectral Images. - Arun M. Saranathan; Mario Parente (IEEE Trans. Geosci. Remote. Sens., 2016)

Estimation of the Intrinsic Dimensionality in Hyperspectral Imagery via the Hubness Phenomenon. - Rob Heylen; Mario Parente; Paul Scheunders (LVA/ICA, 2017)

Pixel purity vertex component analysis. - Rob Heylen; Mario Parente; Paul Scheunders (IGARSS, 2017)

Sparse unmixing with adaptive background. - Yuki Itoh; Mario Parente (IGARSS, 2017)

Unmixing in the presence of nuisances with deep generative models. - Mario Parente; Ian Gemp; Ishan P. Durugkar (IGARSS, 2017)

Semi-Supervised Endmember Identification In Nonlinear Spectral Mixtures Via Semantic Representation. - Yuki Itoh; Siwei Feng; Marco F. Duarte; Mario Parente (CoRR, 2017)

Hyperspectral Band Selection From Statistical Wavelet Models. - Siwei Feng; Yuki Itoh; Mario Parente; Marco F. Duarte (IEEE Trans. Geosci. Remote. Sens., 2017)

Estimation of the Number of Endmembers in a Hyperspectral Image via the Hubness Phenomenon. - Rob Heylen; Mario Parente; Paul Scheunders (IEEE Trans. Geosci. Remote. Sens., 2017)

Semisupervised Endmember Identification in Nonlinear Spectral Mixtures via Semantic Representation. - Yuki Itoh; Siwei Feng; Marco F. Duarte; Mario Parente (IEEE Trans. Geosci. Remote. Sens., 2017)

Perfect Recovery Conditions for Non-negative Sparse Modeling. - Yuki Itoh; Marco F. Duarte; Mario Parente (IEEE Trans. Signal Process., 2017)

New CRISM Data Products for Improved Characterization and Analysis of the Mars2020 Landing Site. - Mario Parente; Yuki Itoh; Arun M. Saranathan (IGARSS, 2019)

Learning Radiative Transfer Models for Climate Change Applications in Imaging Spectroscopy. - Shubhankar Deshpande; Brian D. Bue; David R. Thompson 001; Vijay Natraj; Mario Parente (CoRR, 2019)

Nonlinear Hyperspectral Unmixing With Graphical Models. - Rob Heylen; Vera Andrejchenko; Zohreh Zahiri; Mario Parente; Paul Scheunders (IEEE Trans. Geosci. Remote. Sens., 2019)

On Clustering and Embedding Mixture Manifolds Using a Low Rank Neighborhood Approach. - Arun M. Saranathan; Mario Parente (IEEE Trans. Geosci. Remote. Sens., 2019)

Implementing New Feature Extraction Techniques for Characterization of Complex Mineral Signatures of Salty Regions on Mars. - 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 (IGARSS, 2020)

Classification of Martian Terrains via Deep Clustering of Mastcam Images. - Mario Parente; Tejas Panambur (IGARSS, 2020)

Improved Deep Clustering of Mastcam Images Using Metric Learning. - Tejas Panambur; Mario Parente (IGARSS, 2021)

Sparse Unmixing of Hyperspectral Data: The Legacy of SUnSAL. - Mario Parente; Marian-Daniel Iordache (IGARSS, 2021)

Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images. - Tejas Panambur; Deep Chakraborty; Melissa Meyer; Ralph Milliken; Erik G. Learned-Miller; Mario Parente (CVPR Workshops, 2022)

Improved Self-Supervised Texture Recognition of Mastcam Images by Eliminating Mixed Terrain and Range Patches. - Tejas Panambur; Mario Parente (IGARSS, 2023)

Enhancing Martian Terrain Recognition With Deep Constrained Clustering. - Tejas Panambur; Mario Parente (IEEE Trans. Geosci. Remote. Sens., 2025)