| /external/opencv/cvaux/src/ |
| cvhmm1d.cpp | 443 // var - pointer to the variance vector of the Gaussian pdf
477 // var - two-dimensional pointer to the variance vector of the Gaussian pdf;
479 // the second dimension is indexed along the size of the variance vector
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| batch_normalization_test.cc | 155 auto variance = builder.ConstantR1<float>({6.f, .02f}); local
156 auto sqrt = builder.SqrtF32(variance);
194 auto variance = builder.Div(sum_of_squares, count); local
195 auto standard_deviation = builder.SqrtF32(variance);
617 builder.Parameter(4, var_literal->shape(), "variance");
767 // sum(output_grad * (activation - mean(activation))) / (variance +
802 auto var_parameter = builder.Parameter(3, var_literal->shape(), "variance");
[all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| layers_test.py | [all...] |
| optimizers.py | 336 variance = sq_mean - math_ops.square(mean)
337 std = math_ops.sqrt(math_ops.maximum(epsilon, variance))
367 epsilon: Small value chosen to avoid zero variance.
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| /external/libvpx/libvpx/vpx_dsp/ |
| ssim.c | 329 // content are detected via changes in local variance and local
337 // term 1 -> uses change in scene Variance to weight error score
371 // This measures how much consistent variance is in two consecutive
372 // source frames. 1.0 means they have exactly the same variance.
399 // The reason for the variance and mean terms is the assumption that
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| /external/tensorflow/tensorflow/contrib/quantize/python/ |
| fold_batch_norms_test.py | 80 switches to using frozen mean and variance
150 switches to using frozen mean and variance
215 switches to using frozen mean and variance
279 switches to using frozen mean and variance
356 switches to using frozen mean and variance
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| /cts/apps/CameraITS/tests/dng_noise_model/ |
| dng_noise_model.py | 48 # How large of tiles to use to compute mean/variance.
58 # signal content when computing variance.
128 plt_s.set_ylabel("Variance")
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| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| mvn_diag_test.py | 186 mvn.variance().eval())
194 mvn.variance().eval())
203 mvn.variance().eval())
|
| binomial_test.py | 183 self.assertEqual((3,), binom.variance().get_shape())
184 self.assertAllClose(expected_variances, binom.variance().eval())
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| negative_binomial_test.py | 202 self.assertEqual([3], negbinom.variance().get_shape())
203 self.assertAllClose(expected_vars, negbinom.variance().eval())
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| deterministic.py | 81 (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
238 (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
346 (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
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| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| kalman_filter.py | 178 r"""Compute variance for state transitions.
204 State variance advanced based on `transition_matrices` and
228 predicted_observations: An (observation mean, observation variance) tuple
|
| structural_ensemble.py | 72 `transient` are (typically scalar) Gaussian random variables whose variance is
73 learned from data, and that variance is not time dependent in this
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| /external/tensorflow/tensorflow/python/ops/ |
| nn_grad.py | 743 dv: Backprop for variance, which is
766 grad_x: gradient for x, which is scale * rsqrt(variance + epsilon) *
768 mean(grad_y * (x - mean(x))) / (variance + epsilon)]
773 rsqrt(variance + epsilon)) in training mode;
845 pop_var: A `Tensor` of 1 dimension for the population variance. Only used
847 epsilon: A small float number added to the variance of x.
[all...] |
| /external/ImageMagick/ImageMagick/api/ |
| feature.html | 103 <p>GetImageFeatures() returns features for each channel in the image in each of four directions (horizontal, vertical, left and right diagonals) for the specified distance. The features include the angular second moment, contrast, correlation, sum of squares: variance, inverse difference moment, sum average, sum varience, sum entropy, entropy, difference variance, difference entropy, information measures of correlation 1, information measures of correlation 2, and maximum correlation coefficient. You can access the red channel contrast, for example, like this:</p>
|
| /external/ImageMagick/www/api/ |
| feature.html | 107 <p>GetImageFeatures() returns features for each channel in the image in each of four directions (horizontal, vertical, left and right diagonals) for the specified distance. The features include the angular second moment, contrast, correlation, sum of squares: variance, inverse difference moment, sum average, sum varience, sum entropy, entropy, difference variance, difference entropy, information measures of correlation 1, information measures of correlation 2, and maximum correlation coefficient. You can access the red channel contrast, for example, like this:</p>
|
| feature.php | 103 <p>GetImageFeatures() returns features for each channel in the image in each of four directions (horizontal, vertical, left and right diagonals) for the specified distance. The features include the angular second moment, contrast, correlation, sum of squares: variance, inverse difference moment, sum average, sum varience, sum entropy, entropy, difference variance, difference entropy, information measures of correlation 1, information measures of correlation 2, and maximum correlation coefficient. You can access the red channel contrast, for example, like this:</p>
|
| /external/antlr/antlr-3.4/runtime/Ruby/lib/antlr3/ |
| profile.rb | 84 def variance method in class:ANTLR3.Profile.DataSet
90 sqrt( variance )
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/ |
| OLSMultipleLinearRegression.java | 215 * <p>Calculates the variance-covariance matrix of the regression parameters.
223 * @return The beta variance-covariance matrix
|
| /external/flac/libFLAC/ |
| fixed_intrin_sse2.c | 137 /* 'total_error*' is linearly related to the variance of the residual */
235 /* 'total_error*' is linearly related to the variance of the residual */
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| fixed_intrin_ssse3.c | 131 /* 'total_error*' is linearly related to the variance of the residual */
223 /* 'total_error*' is linearly related to the variance of the residual */
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| /external/libvpx/libvpx/test/ |
| variance_test.cc | 74 * Our codebase calculates the "diff" value in the variance algorithm by
263 // Can be used for MSE, SSE, Variance, etc.
339 // We could sub-class MainTestClass into dedicated class for Variance
344 // Variance tests
373 // Tests related to variance.
496 const uint32_t variance = params_.func(src_, width(), ref_, width(), &sse); local
498 (void)variance;
502 printf("Variance %dx%d time: %5d ms\n", width(), height(),
[all...] |
| /external/libxcam/cl_kernel/ |
| kernel_wavelet_coeff.cl | 3 * Calculate wavelet coefficients variance
5 * output: Wavelet coefficients variance
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| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| sliced_wasserstein_impl.py | 127 mean, variance = nn.moments(patches, [1, 2, 3], keep_dims=True)
128 patches = (patches - mean) / math_ops.sqrt(variance)
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| /external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
| cifar10_input.py | 183 # Subtract off the mean and divide by the variance of the pixels.
246 # Subtract off the mean and divide by the variance of the pixels.
|
