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公开(公告)号：US10412573B2
公开(公告)日：2019-09-10
申请号：US16056098
申请日：2018-08-06
Inventor： Kai Ma , Maohua Chen , Mo Zhao , Zhenxi Qiu , Xiaoming Wu , Nan Cheng , Xiaohui Zheng , Junxiong Chen , Jinheng Xie , Zhe Cheng , Le Yu , Shuhui Mei , Chi Zhang , Huiqin Yang , Yao Qin , Shunfu Ye , Tao Zhang , Wenrong Tang , Yangbin Huang , Ming He , Chaoxiong Diao , Pengbo Zhang , Guanqiao Su , Hongmin Zheng , Xiaojuan Zhang , Zhejin Huang , Xiaoyang Qian , Zhongming Guo , Xiaoyi Fang , Yang Zuo , Yan Dai
IPC: H04W24/00 , H04W8/00 , H04W4/00 , H04B17/318 , H04W4/029 , H04W4/21 , H04W4/80 , H04W64/00 , G06Q50/00 , H04W8/18 , H04W84/12
Abstract: Embodiments of this application provide a near-field wireless communication service processing method performed at a first computing device. While running a social networking application, the first computing device listens to a near-field wireless communication signal broadcasted by a second computing device. After detecting the near-field wireless communication signal broadcasted by the second computing device, first computing device processes the near-field wireless communication signal to obtain identification information associated with the second computing device. The first computing device sends the identification information associated with the second computing device to a remote server supporting the social networking application and obtains a preset service page corresponding to the identification information associated with the second computing device from the server, and displays the preset service page within the social networking application on the first computing device.
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公开(公告)号：US12249076B2
公开(公告)日：2025-03-11
申请号：US17703829
申请日：2022-03-24
Inventor： Luyan Liu , Kai Ma , Yefeng Zheng
Abstract: A method for three-dimensional edge detection includes obtaining, for each of plural two-dimensional slices of a three-dimensional image, a two-dimensional object detection result and a two-dimensional edge detection result, stacking the two-dimensional object detection results into a three-dimensional object detection result, and stacking the two-dimensional edge detection results into a three-dimensional edge detection result. The method also includes performing encoding according to a feature map of the three-dimensional image, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an encoding result, and performing decoding according to the encoding result, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an optimized three-dimensional edge detection result of the three-dimensional image.
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公开(公告)号：US11854205B2
公开(公告)日：2023-12-26
申请号：US17229707
申请日：2021-04-13
Inventor： Shilei Cao , Kai Ma , Yefeng Zheng
CPC classification number: G06T7/11 , G06N3/045 , G06N3/08 , G16H30/40 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004
Abstract: This application relates to a medical image segmentation method, a computer device, and a storage medium. The method includes: obtaining medical image data; obtaining a target object and weakly supervised annotation information of the target object in the medical image data; determining a pseudo segmentation mask for the target object in the medical image data according to the weakly supervised annotation information; and performing mapping on the medical image data by using a preset mapping model based on the pseudo segmentation mask, to obtain a target segmentation result for the target object. Because the medical image data is segmented based on the weakly supervised annotation information, there is no need to annotate information by using much labor during training of the preset mapping model, thereby saving labor costs. The preset mapping model is a model used for mapping the medical image data based on the pseudo segmentation mask.
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公开(公告)号：US12288383B2
公开(公告)日：2025-04-29
申请号：US17955726
申请日：2022-09-29
Inventor： Donghuan Lu , Kai Ma , Yefeng Zheng
IPC: G06V10/774 , G06F18/2415 , G06N3/045 , G06N3/08 , G06T3/40 , G06T7/11 , G06T7/149 , G06V10/40 , G06V10/764 , G06V10/82
Abstract: A method for training an image segmentation model includes calling an encoder to perform feature extraction on a sample image and a scale image to obtain a sample image feature and a scale image feature. The method also includes performing a class activation graph calculation to obtain a sample class activation graph and a scale class activation graph. The method also includes calling a decoder to obtain a sample segmentation result of the sample image, and calling the decoder to obtain a scale segmentation result of the scale image. The method also includes calculating a class activation graph loss and calculating a scale loss. The method also includes training the decoder based on the class activation graph loss and the scale loss.
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公开(公告)号：US12125170B2
公开(公告)日：2024-10-22
申请号：US17706823
申请日：2022-03-29
Inventor： Xinpeng Xie , Jiawei Chen , Yuexiang Li , Kai Ma , Yefeng Zheng
CPC classification number: G06T5/50 , G06T7/97 , G06T2207/20081 , G06T2207/20084
Abstract: An image processing method includes obtaining a sample image and a generative adversarial network (GAN), including a generation network and an adversarial network, and performing style conversion on the sample image, to obtain a reference image. The method further includes performing global style recognition on the reference image, to determine a global style loss between the reference image and the sample image, and performing image content recognition on the reference image and the sample image, to determine a content loss between the reference image and the sample image. The method also includes performing local style recognition on the reference image and the sample image, to determine a local style loss of the reference image and a local style loss of the sample image, training the generation network to obtain a trained generation network, and performing style conversion on a to-be-processed image by using the trained generation network.
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Patent Agency Ranking
公开(公告)号：US11887311B2
公开(公告)日：2024-01-30
申请号：US17388249
申请日：2021-07-29
Inventor： Shilei Cao , Renzhen Wang , Kai Ma , Yefeng Zheng
IPC: G06K9/00 , G06T7/11 , G06T7/194 , G06N3/08 , G06T7/00 , G06F18/25 , G06V10/80 , G06V10/82 , G06V10/42 , G06V10/44
CPC classification number: G06T7/11 , G06F18/253 , G06N3/08 , G06T7/0012 , G06T7/194 , G06V10/42 , G06V10/44 , G06V10/811 , G06V10/82 , G06T2207/20081 , G06T2207/20112
Abstract: Embodiments of this disclosure include a method and an apparatus for segmenting a medical image. The method may include obtaining a slice pair comprising two slices and performing feature extraction on each slice in the slice pair, to obtain high-level feature information and low-level feature information of the each slice in the slice pair. The method may further include segmenting a target object in the each slice according to the low-level feature information and the high-level feature information of the slice, to obtain an initial segmentation result of the each slice and fusing the low-level feature information and the high-level feature information of the slices to obtain a fused feature information. The method may further include determining correlation information between the slices according to the fused feature information and generating a segmentation result of the slice pair based on the correlation information and the initial segmentation results of the slices.
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公开(公告)号：US20250014150A1
公开(公告)日：2025-01-09
申请号：US18891939
申请日：2024-09-20
Inventor： Xinpeng XIE , Jiawei Chen , Yuexiang Li , Kai Ma , Yefeng Zheng
Abstract: In an image processing method, style conversion is performed on a sample image by using a generation network, to obtain a reference image. Style recognition is performed on the reference image by using an adversarial network, to determine a style loss between the reference image and the sample image. Image content recognition is performed on the reference image and the sample image, to determine a content loss between the reference image and the sample image. The generation network is trained based on the style loss and the content loss, to obtain a trained generation network.
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8.发明授权公开(公告)号：US11755121B2
公开(公告)日：2023-09-12
申请号：US17580545
申请日：2022-01-20
Inventor： Xiaolin Hong , Qingqing Zheng , Xinmin Wang , Kai Ma , Yefeng Zheng
CPC classification number: G06F3/017 , G06N3/045 , G06T5/002 , G06T2207/20081 , G06T2207/20084
Abstract: This application provides a gesture information processing method and apparatus, an electronic device, and a storage medium. The method includes: determining an electromyography signal collection target object in a gesture information usage environment; dividing the electromyography signal sample through a sliding window having a fixed window value and a fixed stride into different electromyography signals of the target object, and denoising the different electromyography signals of the target object; recognizing the denoised different electromyography signals, and determining probabilities of gesture information represented by the different electromyography signals; and weighting the probabilities of the gesture information represented by the different electromyography signals, so as to determine gesture information matching the target object.
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公开(公告)号：US20230054751A1
公开(公告)日：2023-02-23
申请号：US17969177
申请日：2022-10-19
Inventor： Luyan Liu , Xiaolin Hong , Kai Ma , Yefeng Zheng
Abstract: A method and an apparatus for classifying an electroencephalogram signal, a device and a computer-readable storage medium. The method includes: obtaining an electroencephalogram signal; performing feature extraction on the electroencephalogram signal to obtain a signal feature corresponding to the electroencephalogram signal; obtaining a difference distribution ratio, the difference distribution ratio being used for representing impacts of difference distributions of different types on distributions of the signal feature and a source domain feature in a feature domain, the source domain feature being a feature corresponding to a source domain electroencephalogram signal; aligning the signal feature with the source domain feature according to the difference distribution ratio to obtain an aligned signal feature; and classifying the aligned signal feature to obtain a motor imagery type corresponding to the electroencephalogram signal.
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公开(公告)号：US20230032683A1
公开(公告)日：2023-02-02
申请号：US17964705
申请日：2022-10-12
Inventor： Donghuan LU , Kai Ma , Yefeng Zheng
Abstract: This application discloses a method for reconstructing a dendritic tissue in an image performed by a computer device. The method includes: acquiring original image data corresponding to a target image of a target dendritic tissue and corresponding reconstruction reference data determined based on a local reconstruction result of the target dendritic tissue in the target image; applying a target segmentation model to the original image data and the reconstruction reference data to acquire a target segmentation result for indicating a target category of each pixel in the target image, and the target category of any pixel being used for indicating whether the pixel belongs to the target dendritic tissue or not; and reconstructing the target dendritic tissue in the target image based on the target segmentation result to obtain a complete reconstruction result of the target dendritic tissue in the target image.
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