Abstract: A method and an electronic device with image data generating are disclosed. The electronic device includes: one or more processors; and memory storing instructions configured to cause the one or more processors to: input an input image to a target model that performs segmenting on the input image to generate a segmented image whose pixels have respective class labels predicted by the target model, calculate an optimization value for the input image based on the segmented image and based on a class label of a first grid area among a plurality of grid areas of a guide image, and optimize the input image based on the optimization value.

Abstract: A method of crowdsourcing annotation for medical image data based on image comparison, includes developing an annotation task; acquiring and verifying medical images according to requirements of the annotation task, and performing statistics on the medical images that meet verification standards to obtain an amount of image data acquired; archiving the medical images that meet the verification standards to form a medical image database; setting up annotation rules, and generating annotation schemes and annotation samples according to the requirements of the annotation task and annotation rules; distributing the medical images in the medical image database to multiple crowdsourcing annotation sides, so that each medical image being annotated by the multiple crowdsourcing annotation sides; annotating, by the crowdsourcing annotation sides, the distributed medical images according to the annotation schemes and the annotation examples to form the annotated images; and merging multiple annotated images correspondi

Abstract: A track fusion method for an unmanned surface vehicle includes: (a) obtaining perception information of the unmanned surface vehicle, where the perception information includes GPS data information and radar data information; (b) pre-processing the radar data information to obtain target radar information; (c) constructing a track correlation model; and performing track correlation between the GPS data information and the target radar information based on the track correlation model; and (d) constructing a fusion data weight allocation model; and subjecting between the GPS data information and the target radar information correlated therewith to track fusion based on the fusion data weight allocation model. This application further provides a track fusion device for unmanned surface vehicles.

Abstract: The present application provides a network user identification method, device and a server. The identification method comprises: jumping from the front-end advertisement environment to a back-end web site environment when a user clicks an advertisement link under a front-end advertisement environment; acquiring a user identifier under the front-end advertisement environment and a user identifier under the back-end web site environment; and determining the identity information of the user based on the front-end user identifier and the back-end user identifier. By adopting the technical scheme, identification of the same user on the same device can be realized under a network environment.