2019
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Murphy, James M; Maggioni, Mauro Unsupervised Clustering and Active Learning of Hyperspectral Images With Nonlinear Diffusion Journal Article IEEE Transactions on Geoscience and Remote Sensing, 57 (3), pp. 1829-1845, 2019, ISSN: 1558-0644. Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral images, imaging, Machine learning, Unsupervised Learning @article{8481477,
title = {Unsupervised Clustering and Active Learning of Hyperspectral Images With Nonlinear Diffusion},
author = {James M Murphy and Mauro Maggioni},
doi = {10.1109/TGRS.2018.2869723},
issn = {1558-0644},
year = {2019},
date = {2019-03-01},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
volume = {57},
number = {3},
pages = {1829-1845},
keywords = {Active Learning, Clustering, diffusion geometry, hyperspectral images, imaging, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Maggioni, Mauro; Murphy, James M Learning by active nonlinear diffusion Journal Article Foundations of Data Science, 1 (“2639-8001-2019-3-271”), pp. 271, 2019, ISSN: A0000-0002. Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @article{2639-8001_2019_3_271,
title = {Learning by active nonlinear diffusion},
author = {Mauro Maggioni and James M Murphy},
url = {http://aimsciences.org//article/id/6f8fefb2-e464-48ea-b2de-f37686725966},
doi = {10.3934/fods.2019012},
issn = {A0000-0002},
year = {2019},
date = {2019-01-01},
journal = {Foundations of Data Science},
volume = {1},
number = {“2639-8001-2019-3-271”},
pages = {271},
keywords = {Active Learning, Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
2018
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Murphy, James M; Maggioni, Mauro Iterative Active Learning with Diffusion Geometry for Hyperspectral Images Inproceedings Proc. of WHISPERS, 2018. Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral images, imaging, Machine learning @inproceedings{whispers2018,
title = {Iterative Active Learning with Diffusion Geometry for Hyperspectral Images},
author = {James M Murphy and Mauro Maggioni},
url = {https://ieeexplore.ieee.org/abstract/document/8747033},
year = {2018},
date = {2018-01-01},
booktitle = {Proc. of WHISPERS},
keywords = {Active Learning, Clustering, diffusion geometry, hyperspectral images, imaging, Machine learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Murphy, James M; Maggioni, Mauro Diffusion geometric methods for fusion of remotely sensed data Inproceedings Velez-Reyes, Miguel; Messinger, David W (Ed.): Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, pp. 137 – 147, International Society for Optics and Photonics SPIE, 2018. Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral images, imaging, Machine learning, Unsupervised Learning @inproceedings{10.1117/12.2305274,
title = {Diffusion geometric methods for fusion of remotely sensed data},
author = {James M Murphy and Mauro Maggioni},
editor = {Miguel Velez-Reyes and David W Messinger},
url = {https://doi.org/10.1117/12.2305274},
doi = {10.1117/12.2305274},
year = {2018},
date = {2018-01-01},
booktitle = {Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV},
volume = {10644},
pages = {137 — 147},
publisher = {SPIE},
organization = {International Society for Optics and Photonics},
keywords = {Active Learning, Clustering, diffusion geometry, hyperspectral images, imaging, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2016
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Wang, Yang; Chen, Guangliang; Maggioni, Mauro High Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies 2016. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @journal{WCM:HSIandMovies,
title = {High Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies},
author = {Yang Wang and Guangliang Chen and Mauro Maggioni},
year = {2016},
date = {2016-01-01},
journal = {IEEE Journal of selected topics in applied Earth observations and remote sensing},
volume = {9},
number = {9},
pages = {4316–4324},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {journal}
}
|
2015
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Maggioni, Mauro Wang Y; Chen, Guangliang Enhanced Detection of Chemical Plumes in Hyperspectral Images and Movies through Improved Background Modeling Inproceedings Proceedings of the 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2015. BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @inproceedings{WangChenMaggioni:Whispers15,
title = {Enhanced Detection of Chemical Plumes in Hyperspectral Images and Movies through Improved Background Modeling},
author = {Mauro Y. Wang Maggioni and Guangliang Chen},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
keywords = {Active Learning, Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2012
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Chen, Guangliang; Iwen, Mark A; Chin, Peter S; Maggioni, Mauro A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements Inproceedings Visual Communications and Image Processing (VCIP), 2012 IEEE, pp. 1-6, 2012. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @inproceedings{6410789,
title = {A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements},
author = {Guangliang Chen and Mark A Iwen and Peter S Chin and Mauro Maggioni},
year = {2012},
date = {2012-01-01},
booktitle = {Visual Communications and Image Processing (VCIP), 2012 IEEE},
pages = {1-6},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Chen, Guangliang; Iwen, Mark A; Chin, Peter S; Maggioni, Mauro A Fast Multiscale Framework for Data in High Dimensions: Measure Estimation, Anomaly Detection, and Compressive Measurements Inproceedings Visual Communications and Image Processing (VCIP), 2012 IEEE, pp. 1-6, 2012. Links | BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @inproceedings{CIMC:vcip2012,
title = {A Fast Multiscale Framework for Data in High Dimensions: Measure Estimation, Anomaly Detection, and Compressive Measurements},
author = {Guangliang Chen and Mark A Iwen and Peter S Chin and Mauro Maggioni},
doi = {10.1109/VCIP.2012.6410789},
year = {2012},
date = {2012-01-01},
booktitle = {Visual Communications and Image Processing (VCIP), 2012 IEEE},
pages = {1-6},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2004
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Maggioni, Mauro; Warner, F J; Davis, Gus L; Coifman, Ronald R; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections Technical Report Yale University Dept. Comp. Sci., (1311), 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @techreport{MMPathTechRep,
title = {Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections},
author = {Mauro Maggioni and F J Warner and Gus L Davis and Ronald R Coifman and Frank B Geshwind and Andreas C Coppi and R A DeVerse},
year = {2004},
date = {2004-02-01},
number = {1311},
address = {Dept. Comp. Sci.},
institution = {Yale University},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {techreport}
}
|
Cassidy, Ryan J; Berger, Jim; Maggioni, Mauro; Coifman, Ronald R Auditory display of hyperspectral colon tissue images using vocal synthesis models Journal Article Proc. 2004 Intern. Con. Auditory Display, 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning @article{AuditoryDisplay,
title = {Auditory display of hyperspectral colon tissue images using vocal synthesis models},
author = {Ryan J Cassidy and Jim Berger and Mauro Maggioni and Ronald R Coifman},
year = {2004},
date = {2004-01-01},
journal = {Proc. 2004 Intern. Con. Auditory Display},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning},
pubstate = {published},
tppubtype = {article}
}
|
Maggioni, Mauro; Warner, F J; Davis, Gus L; Coifman, Ronald R; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections Journal Article submitted, 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @article{MMIEEEPath,
title = {Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections},
author = {Mauro Maggioni and F J Warner and Gus L Davis and Ronald R Coifman and Frank B Geshwind and Andreas C Coppi and R A DeVerse},
year = {2004},
date = {2004-01-01},
journal = {submitted},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|