Advanced New Technologies Co., Ltd.

Alibaba Group Holding Limited

Zhejiang University

Dandan Zheng

Liang Li

Di Wu

Wei Xu

Peng Li

Kunsong Chen

Chongde Sun

Feng Jiang

Xiangzheng Yang

Weinan Huang

A fruit post-harvest disinfection and conveying production line is provided. The production line solves the problem of waxberry type fruits, that is, due to the exposed flesh, it is necessary to minimize the time that water remains on the surface of the fruit during the spraying disinfection process. The fruit post-harvest disinfection and conveying production line includes a workbench, where the workbench is provided with multiple sets of conveyor belts; each set of conveyor belts includes a first conveyor belt and a second conveyor belt; an upper part of a front end of the conveyor belts is provided with an inclined feeding hopper; and the feeding hopper is provided with feeding ports corresponding to each set of conveyor belts.

Fruit post-harvest disinfection and conveying production line

A continuous quantitative spraying structure for sterilization of harvested fruits is provided. The continuous quantitative spraying structure includes a track provided thereon with equally spaced trays for conveying fruits, where the trays each include a circular tray body; a central part of the tray body is provided with a central hole allowing the fruit to fall off; a bottom part of the central hole is provided with two parallel rollers; an inner bottom surface of the tray body is provided with a flap; an inner end of a central shaft of the roller passes through the flap, and is fixed to a rolling wheel; a bearing is provided between the roller and the flap; the track is provided with a spraying sterilization section; the spraying sterilization section is sequentially provided with 3 to 4 sets of sterilization nozzles above a tray conveying route.

Continuous quantitative spraying structure for sterilization of harvested fruit

An information detection method includes: determining key point information in a target identification from a target image based on a preset deep learning algorithm; obtaining an image of the target identification from the target image according to the key point information; and determining information of a preset field from the image of the target identification according to the image of the target identification and a preset identification template matching the target identification.

Information detection method, apparatus, and device

A user identity determining method includes: acquiring target multidimensional feature information of a target user, wherein the target multidimensional feature information includes at least two types of feature information in at least one of biometric feature information or non-biometric feature information; comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result; and determining an identity of the target user based on the comparison result.

User identity determining method, apparatus, and device

Implementations of the present specification disclose a comparison method and apparatus based on a plurality of face image frames and an electronic device. The method includes: obtaining a plurality of face image frames of a target object; selecting a first face image with a highest quality score from the plurality of face image frames, and adding the first face image to a candidate image set; in response to that a number of images in the candidate image set is less than a predetermined value, iteratively selecting, from the plurality of face image frames, a second face image that has a maximum average difference from all face images in the candidate image set in a predetermined parameter, to add the second face image to the candidate image set; and comparing the face images in the candidate image set with a stored face image of the target object.

Comparison method and apparatus based on a plurality of face image frames and electronic device

Methods, systems, and devices, including computer programs encoded on computer storage media, for selecting a target face are provided. One of the methods includes: obtaining at least one facial area including one or more faces in an image taken by a camera; determining, based on the image, a spatial distance between each of the one or more faces and the camera; and selecting, based on the spatial distance, the target face from the one or more faces.

Method and device for face selection, recognition and comparison

Disclosed in the application are document verification and identity verification methods and devices. A computer-implemented document verification method comprises: obtaining an image of a to-be-verified document; and verifying whether an anti-counterfeiting identifier exists in the image; verifying a source of the image; and obtaining a verification result for the to-be-verified document based on the verification of the anti-counterfeiting identifier and the verification of the source of the image. A computer-implemented identity verification method comprises: obtaining an image of an identity document of a to-be-verified user; obtaining a first verification result for the identity document based on the image of the identity document; verifying authenticity of identity information in the image of the identify document to obtain a second verification result; and determining an identity verification result for the to-be-verified user based on the first verification result and the second verification result.

Document verification system, device, and method using a classification model

This specification describes techniques for verifying authenticity of an image. One example method includes identifying a baseline image depicting a baseline background; identifying a comparison image depicting a card; identifying a comparison background in the comparison image, wherein the comparison background is an area of the comparison image other than an area occupied by the card; determining a probability that the baseline background matches the comparison background; determining that the probability satisfies a verification threshold; and in response to determining that the probability satisfies a verification threshold, determining that the comparison image was acquired by capturing an image of a physical card corresponding to the card depicted in the comparison image.

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Beijing, China

Dandan Zheng