Abstract: The present disclosure provides a method and device to process identity information based on a fundus image. An identity information comparison method includes: recognizing a fundus image by using a neural network to obtain a multi-dimensional feature vector representing the identity of a user; comparing the obtained multi-dimensional feature vector with each multi-dimensional feature vector stored in a database; and determining, according to a comparison result, whether there is a matching between the currently obtained multi-dimensional feature vector and a multi-dimensional feature vector pre-stored in the database.

Abstract: The present invention discloses a method, apparatus and system for detecting a fundus image on the basis of machine learning. The method comprises: acquiring a fundus image to be detected; classifying the entire region of the fundus image by using a first classification model to determine whether the fundus image contains a first feature; and if the fundus image does not contain any first feature, classifying a specific region in the fundus image by using at least one second classification model to determine whether the fundus image contains any second feature, wherein the saliency of the first features are greater than that of the second features.

Abstract: The present disclosure provides a method and device to process identity information based on a fundus image. An identity information comparison method includes: recognizing a fundus image by using a neural network to obtain a multi-dimensional feature vector representing the identity of a user; comparing the obtained multi-dimensional feature vector with each multi-dimensional feature vector stored in a database; and determining, according to a comparison result, whether there is a matching between the currently obtained multi-dimensional feature vector and a multi-dimensional feature vector pre-stored in the database.

Abstract: The present disclosure provides a glaucoma image recognition method, device and diagnosis system. The method includes acquiring a fundus image; obtaining an optic disc image and an optic cup image according to the fundus image; obtaining a disc rim image according to the optic disc image and the optic cup image; and determining whether the fundus image is classified as glaucoma according to the disc rim image.

Abstract: The present invention discloses a method, apparatus and system for detecting a fundus image on the basis of machine learning. The method comprises: acquiring a fundus image to be detected; classifying the entire region of the fundus image by using a first classification model to determine whether the fundus image contains a first feature; and if the fundus image does not contain any first feature, classifying a specific region in the fundus image by using at least one second classification model to determine whether the fundus image contains any second feature, wherein the saliency of the first features are greater than that of the second features.