gaussian window Search Results


90
Groupware Technologies Inc sliding windows gaussian linear filter
Supervised Techniques results.
Sliding Windows Gaussian Linear Filter, supplied by Groupware Technologies Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Gaussian inc 0931 for windows
Supervised Techniques results.
0931 For Windows, supplied by Gaussian inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Corning Life Sciences gaussian spatial windowing or bubbles
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
Gaussian Spatial Windowing Or Bubbles, supplied by Corning Life Sciences, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Respiratory Motion gaussian-shaped window function
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
Gaussian Shaped Window Function, supplied by Respiratory Motion, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gaussian-shaped window function - by Bioz Stars, 2026-04
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Gaussian inc 09 for windows
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
09 For Windows, supplied by Gaussian inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/09 for windows/product/Gaussian inc
Average 90 stars, based on 1 article reviews
09 for windows - by Bioz Stars, 2026-04
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Gaussian inc 03 for windows
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
03 For Windows, supplied by Gaussian inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/03 for windows/product/Gaussian inc
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03 for windows - by Bioz Stars, 2026-04
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Gaussian inc gaussview for windows release 3.09
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
Gaussview For Windows Release 3.09, supplied by Gaussian inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/gaussview for windows release 3.09/product/Gaussian inc
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Redis Labs intensity discrimination of gaussian-windowed tones
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
Intensity Discrimination Of Gaussian Windowed Tones, supplied by Redis Labs, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Gaussian inc 0336 for windows software
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
0336 For Windows Software, supplied by Gaussian inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Janssen optimality property of the gaussian window spectrogram
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
Optimality Property Of The Gaussian Window Spectrogram, supplied by Janssen, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Gaussian inc 03w-revision b.02 for windows, version 6
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
03w Revision B.02 For Windows, Version 6, supplied by Gaussian inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Gaussian inc 03w for windows, version 6
The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of <t>Gaussian</t> fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.
03w For Windows, Version 6, supplied by Gaussian inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Supervised Techniques results.

Journal: Sensors (Basel, Switzerland)

Article Title: Human Activity Recognition Data Analysis: History, Evolutions, and New Trends

doi: 10.3390/s22093401

Figure Lengend Snippet: Supervised Techniques results.

Article Snippet: Groupware , Sliding windows Gaussian Linear Filter and Decision Tree classifier , 99.99 , - , - , -.

Techniques: Selection

Unsupervised Techniques results.

Journal: Sensors (Basel, Switzerland)

Article Title: Human Activity Recognition Data Analysis: History, Evolutions, and New Trends

doi: 10.3390/s22093401

Figure Lengend Snippet: Unsupervised Techniques results.

Article Snippet: Groupware , Sliding windows Gaussian Linear Filter and Decision Tree classifier , 99.99 , - , - , -.

Techniques:

The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of Gaussian fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.

Journal: Frontiers in Psychology

Article Title: Evidence for adjustable bandwidth orientation channels

doi: 10.3389/fpsyg.2014.00578

Figure Lengend Snippet: The black dotted lines show the one-dimensional circularly summed classification images for two observers in three conditions . The red lines show the best difference of Gaussian fits to the empirical data. The x -axis in each sub-figure is orientation, the y -axis the weight of the classification image.

Article Snippet: Researchers have used two-dimensional luminance noise most frequently, but studies have also used one-dimensional luminance noise (i.e., noise that is constrained to vary along a single dimension) as well as visual noise that varies in other ways such as color (Gegenfurtner and Kiper, ), motion (Dakin et al., ), orientation (Girshick et al., ), Gaussian spatial windowing or bubbles (Gosselin and Schyns, ), and zero-dimensional noise pedestal increments (Baker and Meese, ).

Techniques:

Fitted difference of Gaussian bandwidth parameters for two observers, AP in circles and MB in triangles . The error bars are 95% confidence intervals on the fitted parameter obtained via the bootstrap. Blue symbols are for the positive, or central Gaussian, and the red symbols the negative or surround Gaussian. R was used to obtain a weighted least squares fit to the parameters as a function of bandwidth. Both increased by roughly 50% for both observers as bandwidth was increased from the narrowest stimulus bandwidth to the widest.

Journal: Frontiers in Psychology

Article Title: Evidence for adjustable bandwidth orientation channels

doi: 10.3389/fpsyg.2014.00578

Figure Lengend Snippet: Fitted difference of Gaussian bandwidth parameters for two observers, AP in circles and MB in triangles . The error bars are 95% confidence intervals on the fitted parameter obtained via the bootstrap. Blue symbols are for the positive, or central Gaussian, and the red symbols the negative or surround Gaussian. R was used to obtain a weighted least squares fit to the parameters as a function of bandwidth. Both increased by roughly 50% for both observers as bandwidth was increased from the narrowest stimulus bandwidth to the widest.

Article Snippet: Researchers have used two-dimensional luminance noise most frequently, but studies have also used one-dimensional luminance noise (i.e., noise that is constrained to vary along a single dimension) as well as visual noise that varies in other ways such as color (Gegenfurtner and Kiper, ), motion (Dakin et al., ), orientation (Girshick et al., ), Gaussian spatial windowing or bubbles (Gosselin and Schyns, ), and zero-dimensional noise pedestal increments (Baker and Meese, ).

Techniques: