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ORCIDStanley R. Rotman
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2020 – today
- 2023
[c17]Eliad Yurkovetsky, Stanley R. Rotman:
Options for Solid Point Target Detection in Hyperspectral Data. IGARSS 2023: 2270-2273- 2022
- [j11]Shiran Havivi, Stanley R. Rotman, Dan G. Blumberg, Shimrit Maman
:
Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data. Sensors 22(24): 9998 (2022) - [c16]Haim Elisha, Stanley R. Rotman:
Hyperspectral Target Detection Using Segmented Matched Filter with Local Covariance Reassignment. WHISPERS 2022: 1-5
2010 – 2019
- 2018
- [j10]Shiran Havivi, Ilan Schvartzman, Shimrit Maman, Stanley R. Rotman, Dan G. Blumberg:
Combining TerraSAR-X and Landsat Images for Emergency Response in Urban Environments. Remote. Sens. 10(5): 802 (2018) - [j9]Shiran Havivi, Ilan Schvartzman, Shimrit Maman, Stanley R. Rotman, Dan G. Blumberg:
Erratum: Havivi, S., et al. Combining TerraSAR-X and Landsat Images for Emergency Response in Urban Environments. Remote Sens. 2018, 10, 802. Remote. Sens. 10(7): 989 (2018) - [c15]O. Faybish, Stanley R. Rotman:
Estimating hyperspectral backgrounds: The need to maintain spectral coherence. IGARSS 2018: 2785-2788 - [c14]Assaf Dvora, Stefania Matteoli, Stanley R. Rotman, Gil Tidhar, Marco Diani, Mayer E. Aladjem:
Hyperspectral Target Detection Using Semi- and Non- Parametric Methods. IGARSS 2018: 2857-2860 - [c13]Yoram Furth, Adi Falik, Stanley R. Rotman:
Stationary Covariance Matrices for Hyperspectral Point Target Detection. IGARSS 2018: 4245-4248 - [c12]Assaf Dvora, Stanley R. Rotman, Mayer E. Aladjem:
Hyperspectral Target Detection Using Tree-Structured Probabilistic Graphical Model and Semi-Parametric Density Estimation. WHISPERS 2018: 1-5 - 2017
- [c11]Stanley R. Rotman, Sapir Ben-Yakar, Dan G. Blumberg:
Background characterization for subpixel target detection. IGARSS 2017: 1344-1346 - [c10]Stanley R. Rotman, Hanoch Shalev:
Evaluating hyperspectral imaging change detection methods. IGARSS 2017: 1946-1949 - 2016
- [j8]Merav Huber-Lerner, Ofer Hadar, Stanley R. Rotman, Revital Huber-Shalem:
Hyperspectral Band Selection for Anomaly Detection: The Role of Data Gaussianity. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 9(2): 732-743 (2016) - [c9]M. M. Dadon, Stanley R. Rotman, D. G. Blumbergn, Steven M. Adler-Golden, Patrick Conforti:
Target detection in the presence of multiple subpixel targets in complex backgrounds. WHISPERS 2016: 1-3 - [c8]Yair Elhadad, Stanley R. Rotman, Dan G. Blumberg:
Analysis of hyperspectral anomaly change detection algorithms. WHISPERS 2016: 1-5 - 2014
- [j7]Merav Huber-Lerner, Ofer Hadar, Stanley R. Rotman, Revital Huber-Shalem:
Compression of Hyperspectral Images Containing a Subpixel Target. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(6): 2246-2255 (2014) - [c7]Sapir Ben-Yakar, Dan G. Blumberg, Stanley R. Rotman:
Advantages and limitations of segmentation for point target detection in hyperspectral imagery. WHISPERS 2014: 1-4 - 2013
- [c6]Marina Hetz, Dan G. Blumberg, Stanley R. Rotman, Roee Enbar, Ariel Benou:
Radar clutter as an indicator for vegetation classification using a single dual polarimetric TSX-1 image. SAR 2013: 88910R - [c5]Gil A. Tidhar, Stanley R. Rotman:
Target detection in inhomogenous non-Gaussian hyperspectral data, based on non-parametric density estimation. WHISPERS 2013: 1-4 - 2012
- [j6]Yuval Cohen, Yitzhak August, Dan G. Blumberg, Stanley R. Rotman:
Evaluating Subpixel Target Detection Algorithms in Hyperspectral Imagery. J. Electr. Comput. Eng. 2012: 103286:1-103286:15 (2012) - [j5]Nir Gorelik, Dan G. Blumberg, Stanley R. Rotman, Dirk Borghys:
Target Detection Using Nonsingular Approximations for a Singular Covariance Matrix. J. Electr. Comput. Eng. 2012: 628479:1-628479:7 (2012) - 2011
- [j4]Benjamin Aminov, Ofir Nichtern, Stanley R. Rotman:
Spatial and temporal point tracking in real hyperspectral images. EURASIP J. Adv. Signal Process. 2011: 30 (2011) - 2010
- [c4]Stanley R. Rotman, Moti Vortman, Cobi Biton:
The impact of band selection on hyperspectral point target detection algorithms. IGARSS 2010: 4761-4763 - [c3]Nir Gorelik, Hadar Yehudai, Stanley R. Rotman:
Anomaly detection in non-stationary backgrounds. WHISPERS 2010: 1-4
2000 – 2009
- 2009
- [c2]C. E. Caefer, Stanley R. Rotman:
Local covariance matrices for improved target detection performance. WHISPERS 2009: 1-4 - 2008
- [j3]Ofir Nichtern, Stanley R. Rotman:
Parameter Adjustment for a Dynamic Programming Track-before-Detect-Based Target Detection Algorithm. EURASIP J. Adv. Signal Process. 2008 (2008) - 2006
- [c1]Joel Lanir, Masha Maltz, Irena Yatskaer, Stanley R. Rotman:
Comparing Multispectral Image Fusion Methods for a Target Detection Task. FUSION 2006: 1-5
1990 – 1999
- 1992
- [j2]C. Goresnic, Stanley R. Rotman:
Texture classification using the cortex transform. CVGIP Graph. Model. Image Process. 54(4): 329-339 (1992) - 1990
- [j1]A. Magid, Stanley R. Rotman, Aryeh M. Weiss:
Comments on Picture thresholding using an iterative selection method. IEEE Trans. Syst. Man Cybern. 20(5): 1238-1239 (1990)
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