V. Velten

发表

Image characterization for automatic target recognition algorithm evaluations

Vincent J. Velten, Lloyd G. Clark, V. Velten, 1991 .

Invariants from Thermophysical Algebraic Infrared Imagery for Object Recognition J. Michel, Member, I€€€, N. Nandhakumar, Senior Member, I€€€, and V. Velten, Member, I€€€

N. Nandhakumar, V. Velten, J. Michel, 1997 .

Thermophysical affine invariants from IR imagery for object recognition

N. Nandhakumar, Johnathan D. Michel, N. Nandhakumar, 1995, Proceedings of the Workshop on Physics-Based Modeling in Computer Vision.

Invariants of the LWIR thermophysical model

V. Velten, D. G. Arnold, K. Sturtz, 1999, Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (CVBVS'99).

Manifold Transfer Subspace Learning ( MTSL ) for High Dimensional Data — Applications to Handwritten Digits and Health Informatics

M. Rizki, M. Raymer, V. Velten, 2017 .

Manifold and transfer subspace learning for cross-domain vehicle recognition in dynamic systems

Mateen M. Rizki, Olga Mendoza-Schrock, Vincent J. Velten, 2015, 2015 18th International Conference on Information Fusion (Fusion).

Exploring EO vehicle recognition performance using manifolds as a function of lighting condition variability

John C. Gallagher, Michael L. Raymer, Edmund G. Zelnio, 2015, Defense + Security Symposium.

Standard SAR ATR evaluation experiments using the MSTAR public release data set

Michael Lee Bryant, Steven W. Worrell, Timothy D. Ross, 1998, Defense, Security, and Sensing.

Manifold Transfer Subspace Learning (MTSL) for Applications in Aided Target Recognition

Mateen M. Rizki, Olga Mendoza-Schrock, Vincent J. Velten, 2017, Int. J. Monit. Surveillance Technol. Res..

Asymptotic modeling of synthetic aperture ladar sensor phenomenology

Edward A. Watson, Brian D. Rigling, Edmund G. Zelnio, 2015, Defense + Security Symposium.

Vehicle engine classification using normalized tone-pitch indexing and neural computing on short remote vibration sensing data

Jie Wei, Zhigang Zhu, Vincent J. Velten, 2019, Expert Syst. Appl..

Review of recent advances in AI/ML using the MSTAR data

Erik Blasch, Edmund G. Zelnio, Vincent J. Velten, 2020, Defense + Commercial Sensing.

Comparison of quantitative analysis techniques to discriminate intimately mixed bidirectional laboratory reflectance spectra

John K. Thomas, Wolfgang Kober, Terry L. Nichols, 1999, Defense, Security, and Sensing.

Automatic machine learning for target recognition

Erik Blasch, Peter Zulch, Uttam Majumder, 2019, Automatic Target Recognition XXIX.

Vehicle classification for civilian and non-civilian applications: A survey

Olga Mendoza-Schrock, Mateen Rizki, Nikolas Bourbakis, 2014, NAECON 2014 - IEEE National Aerospace and Electronics Conference.

ANALYTIC METHODS FOR CODE COMPARISON EVALUATION AND TARGET TEMPERATURE PREDICTION

W. L. Foley, V. Velten, 2007 .

Canonical correlation analysis of LWIR imagery in the frequency domain

John K. Thomas, Wolfgang Kober, Gregory Arnold, 1998, Defense, Security, and Sensing.

Robust thermophysics-based interpretation of radiometrically uncalibrated IR images for ATR and site change detection

N. Nandhakumar, J.D. Michel, D.G. Arnold, 1997, IEEE Trans. Image Process..

Parallax mitigation for hyperspectral change detection

Karmon Vongsy, Michael J. Mendenhall, Michael T. Eismann, 2014, Defense + Security Symposium.