Suzhou Metabrain Intelligent Technology Co., Ltd.

Inspur Suzhou Intelligent Technology Co., Ltd

Jingjing Chen

Ruizhen Wu

Lin Wang

Yongxing Zhang

Ping Huang

Xingyuan Li

Zhen Qin

Disclosed in the present disclosure is a video image coding method. The method includes: dividing an image frame to be coded into a plurality of sub-blocks, and assigning coordinates to each sub-block; calculating a hash value corresponding to an i-th sub-block according to a content of the i-th sub-block; performing a search in a first hash table by using the hash value corresponding to the i-th sub-block; in response to the coordinates of the first reference block being valid, acquiring a content of the first reference block according to the coordinates of the first reference block, and comparing the content of the first reference block with the content of the i-th sub-block; and in response to the content of the first reference block being consistent with the content of the i-th sub-block, performing Intra Block Copy (IBC) coding on the i-th sub-block.

Video image coding method and system, device and medium

A method and apparatus for generating checking data, an electronic device and a non-volatile computer-readable storage medium. The method includes: acquiring a store-status matrix corresponding to a redundant array of independent disks; determining non-reference vectors among the magnetic-disk vectors, and performing data-vector-element evenly dividing processing to an initial data region formed by the non-reference vectors, to obtain first and second data regions; performing data-exchange processing to the first and second data regions in the store-status matrix, to obtain a first matrix; determining a plurality of second-order matrixes in the first and second data regions of the first matrix, and performing position-exchange processing to target magnetic-disk elements in the second-order matrixes, to obtain a second matrix; based on the second matrix, performing single-error-correction encoding generating processing, to obtain first checking data; and based on the second matrix, performing double-error-correction encoding generating processing, to obtain second checking data.

Check data generation method and apparatus, device, and storage medium

A video image interference detection method includes the following steps: acquiring a background image and a current frame image; constructing an edge image of the background image and an edge image of the current frame image respectively; intersecting the edge image of the background image and the edge image of the current frame image to obtain a same boundary image between the edge image of the background image and the edge image of the current frame image; counting a first pixel number in the edge image of the background image and a second pixel number in the same edge image; determining whether the current frame image is interfered according to a ratio of the first pixel number to the second pixel number.

Video image interference detection method, system, device and medium

A method of image recognition includes: acquiring an image training sample data set, where the image training sample data set includes image training sample data and tag information corresponding to the image training sample data; constructing basic activation function and preset bias adjustment function as preset activation function in an addition relationship, determining the preset activation function to be an activation function of a neural network model, to obtain an initial neural network model, where the preset bias adjustment function is a function constructed from a symbol function, a first trainable parameter and a quadratic term in a multiplication relationship; inputting the image training sample data set into the initial neural network model for training until the model converges, to obtain a trained neural network model; when an image to be recognized is acquired, outputting a recognition result corresponding to the image by using the trained neural network model.

Image recognition method and apparatus, and device and medium

Disclosed are a data processing method and apparatus based on an optical neural network, a computer-readable storage medium, and an optical neural network. The method includes: acquiring initial optical information and final output optical information as well as intermediate input optical information and intermediate output optical information at input/output ports of the phase shifter of an input optical signal in a case that beam-splitting ratios of the beam splitters of the two interference optical path structure satisfy a beam-splitting compensation condition; calculating parameters of the internal phase shifters of the two interference optical path structures in a case that the initial optical information and the intermediate input optical information as well as the intermediate output optical information and the final output optical information satisfy a preset beam-splitting condition of the optical neural network; and performing data processing by using the optical neural network based on the parameters.

Optical neural network, data processing method and apparatus based on same, and storage medium

A method for realizing a Hadamard product, a device and a storage medium, includes: acquiring a plurality of to-be-treated optical signals with unequal wavelengths; inputting the to-be-treated optical signals into a wavelength division multiplexer; by using the wavelength division multiplexer, feeding the to-be-treated optical signals to a micro-ring-resonator component, wherein the micro-ring-resonator component includes a plurality of micro-ring-resonator groups each of which is formed by two micro-ring resonators with equal radii; and applying a corresponding electric current to the micro-ring-resonator component, to obtain a result of the Hadamard product according to an outputted light intensity.

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Jiangsu, China

Jingjing Chen