convolution


Also found in: Dictionary, Thesaurus, Legal, Encyclopedia, Wikipedia.
Related to convolution: Fourier transform, Convolution theorem

convolution

 [kon″vo-lu´shun]
a tortuous irregularity or elevation caused by the infolding of a structure upon itself.

con·vo·lu·tion

(kon'vō-lū'shŭn),
1. A coiling or rolling of an organ.
2. Specifically, a gyrus of the cerebral cotex or folia of the cerebellar cortex.
[L. convolutio]

convolution

(kŏn′və-lo͞o′shən)
n.
1. A form or part that is folded or coiled.
2. One of the convex folds of the surface of the brain.

con′vo·lu′tion·al adj.

convolution

(1) A redundancy or folding of tissue native to an organ. 
(2) Gyrus, brain.

convolution

An elevation on the surface of a structure and an infolding of the tissue upon itself

con·vo·lu·tion

(kon-vŏ-lū'shŭn)
1. A coiling or rolling of an organ.
2. Specifically, a gyrus of the cerebral or cerebellar cortex.
[L. convolutio]
References in periodicals archive ?
In the dilated convolution of [17], the same filter can be applied at different receptive fields using different dilation factors by skipping a certain number of input values when applying the filter to a convolutional layer.
For each convolution position on the image a set of 9 anchors having three aspect ratios, three scales and sharing a common center.
Such an interaction may be referred to as a convolution of the original functions.
[9] designed a convolution neural network named DrainNet for removing rain streaks from single image.
By increasing the convolution block of MKNet-A, the classification accuracy can be gradually increased.
Each neuron in convolutional layer is only partially connected to input of current layer, which is equivalent to using a convolutional kernel to perform ergodic convolution to the input feature figure of current layer.
The CNN contains unknown parameters: the filtering coefficients and biases in convolution layers and the weights and biases in fully connected layers.
In the generative network, which is shown in the first row of Figure 3, there are two modules of convolution and deconvolution.
Equation (2) is in fact a two-dimensional convolution product that can also be assessed in the frequency domain.
Generally, the convolution layer is connected to the input layer in a convolutional neural network (CNN).
YOLO does not use region proposal, but directly convolution operations on the whole image, so it is faster than Faster-RCNN in speed, but the accuracy is less than Faster-RCNN.
Ruscheweyh and Sheil-Small [5] proved that the Hadamard product or convolution of two analytic convex functions is also convex analytic and that the convolution of an analytic convex function and an analytic close-to-convex function is close-to-convex analytic in the unit disk E.