gaussian pattern matching (gpm) algorithm Search Results


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( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from <t>log-Gaussian</t> fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.
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( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from <t>log-Gaussian</t> fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.
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( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from <t>log-Gaussian</t> fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.
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( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from <t>log-Gaussian</t> fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.
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Vistec Electron Beam gaussian electron beam writer leica vb6-uhr
( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from <t>log-Gaussian</t> fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.
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Siemens AG xrd patterns
( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from <t>log-Gaussian</t> fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.
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Image Search Results


( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from log-Gaussian fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.

Journal: Scientific Reports

Article Title: Similar contrast sensitivity functions measured using psychophysics and optokinetic nystagmus

doi: 10.1038/srep34514

Figure Lengend Snippet: ( a ) The mean total distance moved by the eye of one observer that was consistent with OKN in the stimulus direction, for 16 drifting noise trials across five spatial frequencies, and eight velocities. Note substantially more OKN consistent motion at lower SFs. ( b ) As ( a ) but showing the total proportion of eye movements consistent with OKN in the stimulus direction (C θ ). ( c ) The optimum velocity (derived from log-Gaussian fits to 6 observers similar to ( b )) as a function of SF. ( d ) As for ( c ) but showing the amplitude of the log-Gaussian fit (a measure of signal-to-noise ratio) which does not show a strong dependence on SF, within observer.

Article Snippet: Patterns were two-dimensional Gaussian noise (made with the randn command in Matlab), filtered to be isotropic and spatial-frequency (SF) band-pass ( ).

Techniques: Derivative Assay