-
公开(公告)号:US11379980B2
公开(公告)日:2022-07-05
申请号:US17097632
申请日:2020-11-13
Inventor: Fangxin Shang , Yehui Yang , Lei Wang , Yanwu Xu
Abstract: The present application discloses an image processing method, an apparatus, an electronic device and a storage medium. A specific implementation is: acquiring an image to be processed; acquiring a grading array according to the image to be processed and a grading network model, where the grading network model is a model pre-trained according to mixed samples, the number of elements contained in the grading array is C−1, C is the number of lesion grades, C lesion grades include one lesion grade without lesion and C−1 lesion grades with lesion, and a kth element in the grading array is a probability of a lesion grade corresponding to the image to be processed being greater than or equal to a kth lesion grade, where 1≤k≤C−1, and k is an integer; determining the lesion grade corresponding to the image to be processed according to the grading array.
-
公开(公告)号:US12026230B2
公开(公告)日:2024-07-02
申请号:US17555723
申请日:2021-12-20
Inventor: Binghong Wu , Yehui Yang , DaLu Yang , Yanwu Xu , Lei Wang , Qian Li
IPC: G06K9/62 , G06F18/213 , G06F18/214 , G06F18/22
CPC classification number: G06F18/2148 , G06F18/213 , G06F18/22
Abstract: Technical solutions relate to the field of artificial intelligence such as deep learning, computer vision and intelligent imaging. A method may includes during training of a one-stage object detecting model, acquiring values of a loss function corresponding to feature maps at different scales respectively in the case that classification loss calculation is required, and the loss function is a focal loss function; and determining a final value of the loss function according to the acquired values of the loss function, and training the one-stage object detecting model according to the final value of the loss function.
-
公开(公告)号:US12093721B2
公开(公告)日:2024-09-17
申请号:US17942696
申请日:2022-09-12
Inventor: Tianfei Wang , Buhe Han , Zhen Chen , Lei Wang
IPC: G06F9/48
CPC classification number: G06F9/4812
Abstract: Provided are a method for processing data, an electronic device and a storage medium, which relate to the field of deep learning and data processing. The method may include: multiple target operators of a target model are acquired; the multiple target operators are divided into at least one operator group, according to an operation sequence of each of the multiple target operators in the target model, wherein at least one target operator in each of the at least one operator group is operated by the same processor and is operated within the same target operation period; and the at least one operator group is output.
-
-