Image filling method and device in FPGA acceleration of convolution neural network

A convolutional neural network, image technology, applied in the field of convolutional neural network FPGA acceleration, can solve problems such as image reduction

Active Publication Date: 2019-03-12
深兰人工智能芯片研究院(江苏)有限公司
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[0009] The embodiment of the present invention provides an image filling method and device in FPGA acceleration of convolutional ne

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  • Image filling method and device in FPGA acceleration of convolution neural network
  • Image filling method and device in FPGA acceleration of convolution neural network
  • Image filling method and device in FPGA acceleration of convolution neural network

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[0061] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0062] The shape and size of the components in the drawings do not reflect the true proportions, and are only intended to illustrate the content of the present invention.

[0063] Such as figure 1 As shown, the convolution algorithm in the prior art makes the output image smaller than the input image.

[0064] In order to solve the above-mentioned problem, the convolution calculation can be performed by using a zero-filling method. Exemplary...

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Abstract

The invention discloses an image filling method and a device in FPGA acceleration of a convolution neural network. The method comprises steps that an image to be processed is acquired; The image to beprocessed is displayed in the form of a first matrix, and each matrix element in the first matrix is one pixel data of the image to be processed. Performing a zero filling process on the first matrixto obtain a second matrix; The first column and the last column of the second matrix are zeros, and each matrix element in the other columns is one pixel data of the image to be processed; Alternatively, the first row and the last row of the second matrix are zero, and each matrix element in the other row is one pixel data of the image to be processed; Performing convolution calculation accordingto the second matrix and convolution weights to obtain a third matrix; The size of the third matrix is the same as the size of the first matrix. In this way, the calculated image can have the same size as the original image.

Description

Technical field [0001] The invention relates to the technical field of convolutional neural network FPGA acceleration, in particular to an image filling method and device in convolutional neural network FPGA acceleration. Background technique [0002] With the development of science and technology, more and more terminals begin to use convolutional neural networks for machine learning to complete image recognition (such as face recognition and object detection) and so on. The essence of Convolutional Neural Network (CNN) is convolution calculation. [0003] In the prior art, the convolution calculation process is as follows: [0004] See figure 1 As shown, it is a schematic diagram of a convolution calculation method for the original image and the convolution weight in the existing technology. Such as figure 1 As shown, the image filling device in the field programmable gate array (Field Programmable Gate Array, FPGA) acceleration of the convolutional neural network will input a 6×...

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Application Information

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IPC IPC(8): G06T3/00G06N3/04
CPCG06T3/0093G06N3/045
Inventor 陈海波
Owner 深兰人工智能芯片研究院(江苏)有限公司
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