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公开(公告)号：US20240185570A1
公开(公告)日：2024-06-06
申请号：US17781182
申请日：2021-06-25
CPC分类号： G06V10/7715 , G06V10/82
摘要： An undecimated image processing method includes: acquiring an image to be processed, inputting the image to be processed into an image processing network, to obtain an output image, where a resolution of the output image is the same with a resolution of the image to be processed. The inputting the image to be processed into the image processing network to obtain the output image includes: inputting the image to be processed into an analysis module to perform feature analysis, and outputting a feature tensor image; inputting the feature tensor image into a processing module, and outputting a processed feature tensor image; and synthesizing, by a synthesis module, at least one feature tensor image outputted by the at least one processing module to obtain the output image.
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公开(公告)号：US20220351333A1
公开(公告)日：2022-11-03
申请号：US17433178
申请日：2020-11-16
IPC分类号： G06T3/40
摘要： The disclosure provides an image reconstruction method for an edge device, an electronic device and a storage medium. The image reconstruction method includes: extracting low-level features from an input image of a first scale to generate first feature maps, the first feature maps having a second scale greater than the first scale as compared with the input image; extracting low-level features from the input image to generate second feature maps, the second feature maps having the second scale; generating mask maps based on the second feature maps; generating intermediate feature maps based on the mask maps and the first feature maps, the intermediate feature maps having the second scale; synthesizing a reconstructed image having the second scale based on the intermediate feature maps. This method facilitates to achieve a better image super-resolution reconstruction effect with lower resource consumption.
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公开(公告)号：US20220319155A1
公开(公告)日：2022-10-06
申请号：US17419726
申请日：2020-12-29
发明人： Yunhua LU , Hanwen LIU , Pablo NAVARRETE MICHELINI , Lijie ZHANG , Dan ZHU
摘要： A method for processing an image is provided, including: acquiring an input image; performing down-sampling and feature extraction on the input image by an encoder network to obtain multiple feature maps; and performing up-sampling and feature extraction on the multiple feature maps by a decoder network to obtain a target segmentation image; processing levels between the encoder network and the decoder network for outputting feature maps with the same resolution are connected with each other, and the encoder network and the decoder network each includes one or more dense calculation blocks, and at least one convolution module in any dense computation block includes at least one group of asymmetric convolution kernels.
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公开(公告)号：US20240233074A9
公开(公告)日：2024-07-11
申请号：US18396866
申请日：2023-12-27
发明人： Pablo NAVARRETE MICHELINI , Wenbin CHEN , Hanwen LIU , Dan ZHU
IPC分类号： G06T3/4046 , G06N3/08 , G06T3/4053 , G06T5/50
CPC分类号： G06T3/4046 , G06N3/08 , G06T3/4053 , G06T5/50
摘要： An image processing method, an image processing device, a training method of a neural network, an image processing method based on a combined neural network model, a constructing method of a combined neural network model, a neural network processor, and a storage medium are provided. The image processing method includes: obtaining, based on an input image, initial feature images of N stages with resolutions from high to low, N is a positive integer and N>2; performing, based on initial feature images of second to N-th stages, cyclic scaling processing on an initial feature image of a first stage, to obtain an intermediate feature image; and performing merging processing on the intermediate feature image to obtain an output image. The cyclic scaling processing includes hierarchically-nested scaling processing of N−1 stages, and scaling processing of each stage includes down-sampling processing, concatenating processing, up-sampling processing, and residual link addition processing.
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5.发明申请公开(公告)号：US20230113318A1
公开(公告)日：2023-04-13
申请号：US17909575
申请日：2021-03-18
IPC分类号： G06N3/09
摘要： A data augmentation method includes: selecting at least two different sets of samples from an original data set, each set of samples including input samples and output samples; generating at least one random number; generating at least one extended input data sample according to input samples in the at least two different sets of samples and the at least one random number; and generating at least one extended output data sample according to output samples in the at least two different sets of samples and the at least one random number, each extended input data sample corresponding to a respective extended output data sample.
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6.发明申请公开(公告)号：US20200226440A1
公开(公告)日：2020-07-16
申请号：US16835809
申请日：2020-03-31
发明人： Dan ZHU , Pablo NAVARRETE MICHELINI , Lijie ZHANG , Hanwen LIU
摘要： Disclosed is a two-dimensional code image generation method and apparatus, a storage medium and an electronic device related to the field of two-dimensional code image technology. The method includes obtaining an initial two-dimensional code image and a background image, and performing structured processing on the initial two-dimensional code image according to the background image to obtain a structured two-dimensional code image, performing mode transfer processing on the background image to obtain a background image of a target mode by a mode transfer model, and performing a fusion operation on the structured two-dimensional code image and the background image of the target mode to obtain a target two-dimensional code image.
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公开(公告)号：US20190332367A1
公开(公告)日：2019-10-31
申请号：US16201143
申请日：2018-11-27
摘要： A method and an apparatus for installing an application are disclosed. The method comprises: receiving a request to install the application; triggering running of a script to obtain installation information of the selected application and a target virtual environment corresponding to the selected application; processing the installation information of the selected application according to compiling rules and installing rules corresponding to the installation information and the target virtual environment to cause the selected application to be installed into the target virtual environment.
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公开(公告)号：US20240244221A1
公开(公告)日：2024-07-18
申请号：US18558741
申请日：2023-01-04
IPC分类号： H04N19/137 , H04N19/105 , H04N19/132 , H04N19/176 , H04N19/33
CPC分类号： H04N19/137 , H04N19/105 , H04N19/132 , H04N19/176 , H04N19/33
摘要： An image processing method includes: obtaining a current image frame and a reference image frame; sequentially performing downsampling and upsampling on the current image frame to obtain a processed current image frame, and sequentially performing downsampling and upsampling on the reference image frame to obtain a processed reference image frame; according to a preset division manner, dividing the processed current image frame into current image sub-blocks and dividing the processed reference image frame into reference image sub-blocks; determining a reference image sub-block with a minimum similarity to each current image sub-block among the reference image sub-blocks as a matching block of the current image sub-block; obtaining a motion vector corresponding to the current image sub-block based on each current image sub-block and the matching block corresponding to the current image sub-block; and encoding the current image frame based on the motion vector.
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9.发明申请公开(公告)号：US20210407041A1
公开(公告)日：2021-12-30
申请号：US17281291
申请日：2020-05-28
发明人： Hanwen LIU , Pablo NAVARRETE MICHELINI , Dan ZHU , Lijie ZHANG
摘要： Disclosed are an image processing method and device, a training method of a neural network and a storage medium. The image processing method includes: obtaining an input image, and processing the input image by using a generative network to generate an output image. The generative network includes a first sub-network and at least one second sub-network, and the processing the input image by using the generative network to generate the output image includes, processing the input image by using the first sub-network to obtain a plurality of first feature images; performing a branching process and a weight sharing process on the plurality of first feature images by using the at least one second sub-network to obtain a plurality of second feature images; and processing the plurality of second feature images to obtain the output image.
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公开(公告)号：US20210209459A1
公开(公告)日：2021-07-08
申请号：US16073195
申请日：2018-01-19
摘要： Provided are a processing method and system for a convolutional neural network, and a computer-readable medium, the processing method includes training a generator and training a discriminator, wherein training a generator includes: extracting a low-resolution color image from a high-resolution color image; training parameters of a generator network, by using the low-resolution color image and a noise image as an input image, based on parameters of a discriminator network, and reducing a generator cost function training a discriminator includes: inputting an output image of the trained generator network and the high-resolution color image to the discriminator network, respectively; training parameters of the discriminator network by reducing a discriminator cost function (S204) the generator cost function and the discriminator cost function represent a degree in which the output image of the generator network corresponds to the high-resolution color image.
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