Methods and systems are disclosed for performing operations comprising: detecting, by a messaging application, purchase or possession of a physical item by a user; identifying an augmented reality experience related to the physical item; in response to detecting purchase or possession of the physical item, granting the messaging application to the augmented reality experience; capturing, by a camera of a client device associated with the user, an image that depicts the physical item; and applying one or more augmented reality elements associated with the augmented reality experience to the image of the physical item.

Aspects of the disclosure relate to detecting and identifying malicious sites using machine learning. A computing platform may receive a uniform resource locator (URL). The computing platform may parse and/or tokenize the URL to reduce the URL into a plurality of components. The computing platform may identify human-engineered features of the URL. The computing platform may compute a vector representation of the URL to identify deep learned features of the URL. The computing platform may concatenate the human-engineered features of the URL to the deep learned features of the URL, resulting in a concatenated vector representation. By inputting the concatenated vector representation of the URL to a URL classifier, the computing platform may compute a phish classification score. In response to determining that the phish classification score exceeds a first phish classification threshold, the computing platform may cause a cybersecurity server to perform a first action.

The present disclosure provides a logo picture processing method, apparatus, device and medium, and relates to technical field of image processing, and specifically to the technical field of artificial intelligence such as deep learning and computer vision. The logo picture processing method includes: obtaining a logo picture including: a current logo graph and current text information; performing text recognition on the logo picture to obtain the current text information; searching for a picture that matches both the current logo graph and the current text information, to obtain a matched picture. The present disclosure may improve the accuracy of the matched picture of the logo picture and thereby improve the logo picture recognition accuracy.

Techniques for template generation from image content includes extracting information associated with an input image. The information comprises: 1) layout information indicating positions of content corresponding to a content type of a plurality of content types within the input image; and 2) text attributes indicating at least a font of text included in the input image. A user-editable template having the characteristics of the input image is generated based on the layout information and the text attributes.

A system receives an image including a live facial image of the user and an identity document including a photograph of the user. Moreover, the system calculates a facial match score by comparing facial features in the live facial image to facial features in the photograph. The system recognizes data objects and characters in the identity document using optical character recognition (OCR) and computer vision, and then identifies, based on the recognized data objects and characters, a type of the identity document. Further, the system calculates a document validity score by comparing the recognized characters and data objects to character strings and data objects known to be present in the identified type of the identity document. Additionally, the system determines and outputs the user's identity verification status based on comparing the facial match score to a facial match threshold and comparing the document validity score to a document validity threshold.

A method and system are provided for assigning metadata candidates to a commercial by performing image analysis on a plurality of the video frames to identify video frames that include one or more of identifiable product-related logos, brand-related logos, product-related text, or brand-related text which appear in the video frames, capturing frame data for such video frames, categorizing a temporal position of the identified video frames within the commercial as being in either a beginning or ending portion of the commercial, or a middle portion of the commercial, and assigning to the commercial the identified products or brands as primary metadata candidates when the temporal position of the identified video frames within the commercial is in either the beginning or ending portion of the commercial.

Methods and systems are disclosed for performing operations comprising: receiving an image that includes a depiction of a person wearing a fashion item; generating a segmentation of the fashion item by the person depicted in the image; receiving voice input associated with the person depicted in the image; in response to receiving the voice input, generating one or more augmented reality elements representing the voice input; and applying the one or more augmented reality elements to the fashion item worn by the person based on the segmentation of the fashion item worn by the person.

An apparatus for automatically evaluating chassis or wheel alignment measurement data comprises: a memory device configured to store a number of chassis data records, with each chassis data record containing at least one chassis parameter and a tolerance range allocated to each chassis parameter; a provisioning device configured to provide a data record of current chassis parameters, which comprises at least one current chassis parameter; a selection device configured to select, on the basis of the data record provided by the provisioning device, a subset of chassis data records from the chassis data records stored in the memory device; and a determination device configured to determine the proportion of the chassis data records from the subset of chassis data records for which the current chassis parameter's of the data record provided by the provisioning device are within the specified tolerance ranges.

Aspects of the detailed technologies concern training and use of neural networks for fine-grained classification of large numbers of items, e.g., as may be encountered in a supermarket. Mitigating false positive errors is an exemplary area of emphasis. Novel network topologies are also detailed—some employing recognition technologies in addition to neural networks. A great number of other features and arrangements are also detailed.

A system and method for forming a medical implant using a printing device. The printing device includes a print head having a heated nozzle, a heated build plate for receiving the printed material thereon, and a reflective plate having an active heater. A method for forming a medical device includes extruding a printing material by contiguous deposition to form a porous object having a lattice-like structure. The medical device, such as a spinal implant, may have interconnected pores and different regions, each having a different porosity for encouraging bone growth therein. The printed medical implant may be designed to be patient-specific, customized, and printed on-demand.