Search Results - "Bajorski, P."

Analytical Comparison of the Matched Filter and Orthogonal Subspace Projection Detectors for Hyperspectral Images by Bajorski, P.

“…In this paper, we perform an analytical comparison of two well-known detectors-the matched filter detector (MFD) and the orthogonal subspace projection (OSP)…”
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Second Moment Linear Dimensionality as an Alternative to Virtual Dimensionality by Bajorski, P

“…In an effort to assess the effective linear dimensionality of hyperspectral images, a notion of virtual dimensionality (VD) has been developed, and it is being…”
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Statistical Inference in PCA for Hyperspectral Images by Bajorski, P

“…Principal component analysis (PCA) is a popular tool for initial investigation of hyperspectral image data. There are many ways in which the estimated…”
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Generalized Detection Fusion for Hyperspectral Images by Bajorski, P.

“…The purpose of this paper is to introduce a general type of detection fusion that allows combining a set of basic detectors into one more versatile detector…”
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Optimization of Amount and Blending of Cementitious Materials in High-Performance Concrete by Bajorski, Peter, Streeter, Donald A.

“…In recent years, there has been a demand by the traveling public for longer-lasting, more durable transportation structures. One of the biggest problems…”
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Efficient tagging of visual fixations from mobile eye trackers using hierarchical clustering for batch processing by Kinsman, T., Bajorski, P., Pelz, J. B.

“…Abstract only…”
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Impact of material abundances distributions on detection power in hyperspectral images by Bajorski, P.

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Nonparametric Two-Sample Comparisons of Changes on Ordinal Responses by Bajorski, Peter, Petkau, John

“…We discuss two-armed clinical trials in which an ordinal response is observed on entry and at follow-up. In certain subject areas, such data are often reduced…”
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Min-max detection fusion for hyperspectral images by Bajorski, P.

“…We propose an alternative formulation for an already known approach of continuum fusion of detectors. Our approach is based on min-max and max-min detectors…”
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Directional segmented matched filter for hyperspectral images by Bajorski, P.

“…We propose a new type of a segmented matched filter, called a directional segmented matched filter (DSMF), based on geometric considerations between the…”
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On the reliability of PCA for complex hyperspectral data by Bajorski, P.

“…Principal Component Analysis (PCA) is a popular tool for initial investigation of hyperspectral image data. There are many ways in which the estimated…”
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Nonnegative principal components for hyperspectral imaging by Bajorski, P.

“…The classic PCA (Principal Component Analysis) has been applied in hyperspectral imaging with varying success. One obstacle in its application is the potential…”
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Simplex projection methods for selection of endmembers in hyperspectral imagery by Bajorski, P.

“…It is well known that performance of subpixel target detection algorithms depends on the choice of endmembers used to characterize the background and the…”
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Use of clustering with partial least squares regression for predictions based on hyperspectral data by Bajorski, P., Kazmierowski, C., Cierniewski, J., Piekarczyk, J., Kusnierek, K., Krolewicz, S., Terelak, H., Stuczynski, T., Maliszewska-Kordybach, B.

“…Visible and near-infrared (VNIR) diffuse reflectance spectroscopy (DRS) has proven to be effective tools of estimation of soil properties. Regression models…”
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Hierarchical image clustering for analyzing eye tracking videos by Kinsman, T, Bajorski, P, Pelz, J B

“…The classification of a large number of images is a familiar problem to the image processing community. It occurs in consumer photography, bioinformatics,…”
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Analytical treatment of detection power in simulated hyperspectral images by Bajorski, P.

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Geometric basis-vector selection methods and subpixel target detection as applied to hyperspectral imagery by Bajorski, P., Ientilucci, E.J.

“…In this paper, we compare three basis-vector selection methods as applied to subpixel target detection. This is a continuation of previous research in which a…”
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