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1.发明公开公开(公告)号：US20230186566A1
公开(公告)日：2023-06-15
申请号：US17613487
申请日：2020-10-30
发明人： Chan Zeng , Ge Li , Guanju Cheng , Peng Gao , Guotong Xie
CPC分类号： G06T19/00 , G06T7/73 , G06T5/002 , G06T7/0012 , G06T2207/10081 , G06T2207/30012 , G06T2207/20084 , G06T2200/04 , G06T2219/004
摘要： The present disclosure provides a method of positioning vertebra in a CT image, an apparatus, a computer device, and a computer readable storage medium. The method includes: pre-processing vertebra CT image data; inputting the pre-processed vertebra CT image data into a pre-trained neural network to obtain regression results of heat maps of key points corresponding to the pre-processed vertebra CT image data; regressing of 3D heat maps corresponding to the positions of the key points of the vertebra mass center based on the regression results of the heat maps of the key points and the pre-processed vertebra CT image data; serving 3D heat maps corresponding to the positions of the key points of the vertebra mass center as labels, and networked regressing 3D heat map information to position the vertebra. Effects caused by scanning machine difference and scanning noise are avoided, and the vertebra with complex forms is accurately positioned.
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公开(公告)号：US12086982B2
公开(公告)日：2024-09-10
申请号：US17612566
申请日：2020-10-30
发明人： Ge Li , Guanju Cheng , Chan Zeng , Peng Gao , Guotong Xie
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/12 , G06T7/62 , G06T2207/20084 , G06T2207/30041
摘要： The present disclosure relates to an artificial intelligence field using a neural network, and publishes a method for confirming a cup-disc ratio based on a neural network, an apparatus, a computer device, and a computer readable storage medium. The method includes: obtaining a retinal image, and detecting an optical disc region in the retinal image to obtain the optical disc region; inputting the optical disc region into a pre-trained neural network to obtain a prediction cup-disc ratio and segment images of an optical cup and an optical disc; computing a cup-disc ratio based on the segment images of the optical cup and the optical disc; and confirming a practical cup-disc ratio based on the prediction cup-disc ratio and the computed cup-disc ratio.
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公开(公告)号：US20220309654A1
公开(公告)日：2022-09-29
申请号：US17612566
申请日：2020-10-30
发明人： Ge Li , Guanju Cheng , Chan Zeng , Peng Gao , Guotong Xie
摘要： The present disclosure relates to an artificial intelligence field using a neural network, and publishes a method for confirming a cup-disc ratio based on a neural network, an apparatus, a computer device, and a computer readable storage medium. The method includes: obtaining a retinal image, and detecting an optical disc region in the retinal image to obtain the optical disc region; inputting the optical disc region into a pre-trained neural network to obtain a prediction cup-disc ratio and segment images of an optical cup and an optical disc; computing a cup-disc ratio based on the segment images of the optical cup and the optical disc; and confirming a practical cup-disc ratio based on the prediction cup-disc ratio and the computed cup-disc ratio.
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公开(公告)号：US11972601B2
公开(公告)日：2024-04-30
申请号：US17614070
申请日：2020-08-28
IPC分类号： G06V10/774 , G06N3/084 , G06V10/25 , G06V10/26 , G06V10/762 , G06V10/77 , G06V10/80 , G06V10/82 , G06V20/70
CPC分类号： G06V10/774 , G06N3/084 , G06V10/25 , G06V10/267 , G06V10/763 , G06V10/7715 , G06V10/806 , G06V10/82 , G06V20/70
摘要： The present disclosure relates to a technology field of artificial intelligence and provides a method for selecting image samples and related equipment. The method trains an instance segmentation model with first image samples and trains a score prediction model with third image samples. An information quantum score of second image samples is calculated through the score prediction model and feature vectors extracted. The second image samples are clustered according to the feature vectors of the second image samples and sample clusters of the second image samples are obtained. Target image samples are selected from the second image samples according to the information quantum score of the second image samples and the sample clusters. Target image samples from the image samples are selected for labelling, improving an accuracy of sample selection.
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公开(公告)号：US20220415087A1
公开(公告)日：2022-12-29
申请号：US17620733
申请日：2020-05-29
发明人： Ge Li , Rui Wang , Lilong Wang , Yijun Tang , Meng Zhang , Peng Gao
IPC分类号： G06V40/18 , G06T7/73 , G06T7/60 , G06V10/98 , G06V10/774 , G06V10/82 , G06V10/776
摘要： The application relates to the technical field of artificial intelligence, and provides a method, device, electronic equipment and storage medium for positioning macular center in fundus images. The method comprises: acquiring a detection result of the fundus image detection model, wherein the detection result includes an optic disc area, and a first detection block and a first confidence score corresponding to the optic disc area, and a macular area, and a second detection block and a second confidence score corresponding to the macular area; calculating a center point coordinate of the optic disc area according to the first detection block, and calculating a center point coordinate of the macular area according to the second detection block; identifying whether the to-be-detected fundus image is a left eye fundus image or a right eye fundus image, and correcting a center point of the macular area using different correction models.
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公开(公告)号：US20220230417A1
公开(公告)日：2022-07-21
申请号：US17614070
申请日：2020-08-28
IPC分类号： G06V10/774 , G06V10/26 , G06V10/82 , G06V10/762 , G06V10/77 , G06V10/80 , G06V10/25 , G06V20/70 , G06N3/08
摘要： The present disclosure relates to a technology field of artificial intelligence and provides a method for selecting image samples and related equipment. The method trains an instance segmentation model with first image samples and trains a score prediction model with third image samples. An information quantum score of second image samples is calculated through the score prediction model and feature vectors extracted. The second image samples are clustered according to the feature vectors of the second image samples and sample clusters of the second image samples are obtained. Target image samples are selected from the second image samples according to the information quantum score of the second image samples and the sample clusters. Target image samples from the image samples are selected for labelling, improving an accuracy of sample selection.
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7.发明授权公开(公告)号：US11928782B2
公开(公告)日：2024-03-12
申请号：US17613487
申请日：2020-10-30
发明人： Chan Zeng , Ge Li , Guanju Cheng , Peng Gao , Guotong Xie
CPC分类号： G06T19/00 , G06T5/70 , G06T7/0012 , G06T7/73 , G06T2200/04 , G06T2207/10081 , G06T2207/20084 , G06T2207/30012 , G06T2219/004
摘要： The present disclosure provides a method of positioning vertebra in a CT image, an apparatus, a computer device, and a computer readable storage medium. The method includes: pre-processing vertebra CT image data; inputting the pre-processed vertebra CT image data into a pre-trained neural network to obtain regression results of heat maps of key points corresponding to the pre-processed vertebra CT image data; regressing of 3D heat maps corresponding to the positions of the key points of the vertebra mass center based on the regression results of the heat maps of the key points and the pre-processed vertebra CT image data; serving 3D heat maps corresponding to the positions of the key points of the vertebra mass center as labels, and networked regressing 3D heat map information to position the vertebra. Effects caused by scanning machine difference and scanning noise are avoided, and the vertebra with complex forms is accurately positioned.
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公开(公告)号：US12002473B2
公开(公告)日：2024-06-04
申请号：US17617314
申请日：2020-12-24
发明人： Yuechao Guo , Yixuan Qiao , Yijun Tang , Jun Wang , Peng Gao , Guotong Xie
摘要： A voiceprint recognition method includes: obtaining a target speech information set to be recognized that includes speech information corresponding to at least one object; extracting target feature information from the target speech information set by using a preset algorithm, and optimizing the target feature information based on a first loss function to obtain a first voiceprint recognition result; obtaining target speech channel information of a target speech channel, where the target speech channel information includes channel noise information, and the target speech channel is used to transmit the target speech information set; extracting target feature vectors in the channel noise information, and optimizing the target feature vectors based on a second loss function to obtain a second voiceprint recognition result; and fusing the first voiceprint recognition result and the second voiceprint recognition result to determine a final voiceprint recognition result.
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9.发明授权公开(公告)号：US11798563B2
公开(公告)日：2023-10-24
申请号：US17617296
申请日：2020-08-26
发明人： Yuechao Guo , Yixuan Qiao , Yijun Tang , Jun Wang , Peng Gao , Guotong Xie
摘要： A method for voiceprint recognition of an original speech is used to reduce information losses and system complexity of a model for data recognition of a speaker's original speech. The method includes: obtaining original speech data, and segmenting the original speech data based on a preset time length to obtain segmented speech data; performing tail-biting convolution processing and discrete Fourier transform on the segmented speech data through a preset convolution filter bank to obtain voiceprint feature data; pooling the voiceprint feature data through a preset deep neural network to obtain a target voiceprint feature; performing embedded vector transformation on the target voiceprint feature to obtain corresponding voiceprint feature vectors; and performing calculation on the voiceprint feature vectors through a preset loss function to obtain target voiceprint data, where the loss function includes a cosine similarity matrix loss function and a minimum mean square error matrix loss function.
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