The present application provides a method and system for extracting nail contours. The method is based on the system and comprises: the step of data acquisition: carrying out 3D scanning to obtain finger 3D data of a target finger, wherein the finger 3D data include complete nail 3D data: the step of point cloud processing of data: converting the finger 3D data converted into 3D point cloud data to obtain a finger point cloud, wherein the finger point cloud includes a nail curved-surface point cloud; the step of nail point cloud acquisition: segmenting the finger point cloud to obtain the nail curved-surface point cloud; the step of nail point cloud flattening: flattening the nail curved-surface point cloud in an equal surface area manner to obtain a nail plane point cloud in a planar state; and the step of nail contour drawing: drawing a nail contour according to the contour of the nail plane point cloud. According to the method and system for extracting nail contours, the nail plane point cloud formed after the nail curved-surface point cloud of the curved nail is flattened is obtained, and the shape of an outer contour point cloud of the flattened nail plane point cloud better fits the outer contour of the curved nail.

A method for clustering phishing web resources based on visual content image, executed on a computer device comprising at least a processor and memory, and the method comprises the following steps: receiving references to a set of phishing web resources; retrieving at least one image of the visual content of each web resource of the set; processing the content of each visual content image associated with one of the set web resources, while contouring the elements on each image of the phishing web resource visual content; filtering the identified contours in each visual content image by removing the identical contours; combining the web resource associated with the compared contours and the cluster based on pairwise comparison of the identified contours and cluster contours, wherein, if the similarity value overrides the threshold value, otherwise, creating a new cluster for the web resource; storing references to web resources associated with corresponding contours of the content from a set of specified clusters in a database.

A filling rate measurement method includes: obtaining a space three-dimensional model generated by measuring a first storage having an opening and a first storage space in which a measurement target is to be stored, the measuring being performed using a range sensor facing the first storage; obtaining a storage three-dimensional model that is a three-dimensional model of the first storage in which the measurement target is not stored; extracting a target portion corresponding to the measurement target from the space three-dimensional model using the space three-dimensional model and the storage three-dimensional model; calculating a first three-dimensional coordinate system; estimating a target three-dimensional model using the target portion and the first three-dimensional coordinate system, the target three-dimensional model being a three-dimensional model of the measurement target in the first storage space; and calculating a first filling rate of the measurement target with respect to the first storage space.

A processor, method, and non-transitory computer-readable storage medium for processing template data and search data according to a search window applied to the search data. The search window comprising a set of offset positions. The processing is performed by a block matching engine (BME) that produces a tensor with difference values, and a convolutional engine (CE) that performs a convolutional operation on the tensor. The processing is performed in an iterative interleaved fashion, by dividing the set of offset positions into a plurality of subsets of offset positions. In parallel with processing of the first X offset positions by the CE, the BME generates the next X channels of the tensor, and which are subsequently pipelined through to the CE via an internal storage, etc.

A computer-implemented method for processing an electronic image may include receiving, by an artificial intelligence (AI) system at an electronic storage of the AI system, one or more digital whole slide images (WSIs) and extracting one or more vectors of features from one or more foreground tiles of tile images of the one or more digital WSIs. The method may include running a trained machine learning model on the one or more vectors of features and determining, based on an output of the trained machine learning model, whether one or more quality issues are present in the one or more digital WSIs.