A system, method and computer program product for accessing content based on an image. The method comprises comparing an image to a database of images, each of the images of the database being associated with at least one corresponding audio track, identifying those ones images of the database that correspond to the image, and identifying the at least one corresponding audio track that corresponds to the identified images. In one example aspect, the method also comprises presenting the audio track to a user. Corresponding metadata also can be presented. The images may be classified by, e.g., genre, musical album, concept, or the like, and, in cases where an input image is determined to belong to any such classes, audio content and/or metadata relating thereto are identified and presented to the user.

A system for selecting an image to accompany text from a user in connection with a social media post. The system is capable of receiving text from the user, identifying one or more search terms based on the text, identifying candidate images from images in one or more image databases using the search terms, presenting one or more candidate images to the user, receiving from the user a selected image from the one or more candidate images, generating the social media post comprising the selected image and the user-submitted text, and transmitting the social media post for display.

A system for selecting an image to accompany text from a user in connection with a social media post. The system is capable of receiving text from the user, identifying one or more search terms based on the text, identifying candidate images from images in one or more image databases using the search terms, presenting one or more candidate images to the user, receiving from the user a selected image from the one or more candidate images, generating the social media post comprising the selected image and the user-submitted text, and transmitting the social media post for display.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for contextually disambiguating queries are disclosed. In an aspect, a method includes receiving an image being presented on a display of a computing device and a transcription of an utterance spoken by a user of the computing device, identifying a particular sub-image that is included in the image, and based on performing image recognition on the particular sub-image, determining one or more first labels that indicate a context of the particular sub-image. The method also includes, based on performing text recognition on a portion of the image other than the particular sub-image, determining one or more second labels that indicate the context of the particular sub-image, based on the transcription, the first labels, and the second labels, generating a search query, and providing, for output, the search query.

A system, a method and a non-transitory computer readable storage medium for base calling are described. The base calling method includes processing through a neural network first image data comprising images of clusters and their surrounding background captured by a sequencing system for one or more sequencing cycles of a sequencing run. The base calling method further includes producing a base call for one or more of the clusters of the one or more sequencing cycles of the sequencing run.

A computer-implemented method is provided. The method includes: obtaining a sample text and a sample image corresponding to the sample text; labeling a true semantic tag for the sample text according to a first preset rule; obtaining a text feature representation of the sample text and a predicted semantic tag output by a text coding sub-model; obtaining an image feature representation of the sample image output by an image coding sub-model; calculating a first loss based on the true semantic tag and the predicted semantic tag; calculating a contrast loss based on the text feature representation of the sample text and the image feature representation of the sample image; adjusting parameters of the text coding sub-model based on the first loss and the contrast loss; and adjusting parameters of the image coding sub-model based on the contrast loss.

A server comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to obtain transfer records identifying value transfers associated with an account of a user, the transfer records including a transfer amount, a transfer date and a transfer descriptor; group the transfer records based on predefined criteria; within at least one group of the transfer records, identify one or more representative transfer records based at least on stored selection criteria; obtain an image associated with at least one of the representative transfer records; and send, via the communications module and to a computing device associated with the user, a transfer record summary interface, the transfer record summary interface including the image associated with the at least one representative transfer record.

Implementations are described herein for automatically annotating or curating digital images using various signals generated by individual users, in addition to or instead of content of the digital images themselves, thereby to enable the digital images to be retrieved from a searchable database based on their annotations. In particular, techniques are described herein for identifying events associated with a user, e.g., based on natural language input provided by a user, and automatically classifying/annotating images inferred to be related to those events.

Implementations are described herein for automatically annotating or curating digital images using various signals generated by individual users, in addition to or instead of content of the digital images themselves, thereby to enable the digital images to be retrieved from a searchable database based on their annotations. In particular, techniques are described herein for identifying events associated with a user, e.g., based on natural language input provided by a user, and automatically classifying/annotating images inferred to be related to those events.

A method and system for providing on-demand updating of metadata information associated with clinical image data files is disclosed. The system allows for extracting, on the fly, additional metadata fields from clinical image data files and re-indexing the metadata to include the additional fields so that an end-user can perform operations (e.g., searching, browsing, etc.) based on the newly indexed fields. The metadata fields may be defined in a configurable schema file (e.g., XML, YML, etc.). The system can gain efficiencies by, for example, reading only a subset of the DICOM file (e.g., reading only the first few kilobytes that contain the header), scanning only a subset of source data folders, etc.