Computer-implemented techniques for sematic image retrieval. According to one technique, digital images are classified into N number of categories based on their visual content. The classification provides a set of N-dimensional image vectors for the digital images. Each image vector contains up to N number of probability values for up to N number of corresponding categories. An N-dimensional image match vector is generated that projects an input keyword query into the vector space of the set of image vectors by computing the vector similarities between a word vector for the input query and a word vector for each of the N number of categories. Vector similarities between the image match vectors and the set of image vectors can be computed to determine images semantically relevant to the input query.

Disclosed is a system for tracking user activities with a user identification tag stored at the user's Internet-capable device. For example, the system can store a pixel having a color scheme that identifies the user but that is hidden to the user and identifiable by an external computer. The pixel can be stored in the user device's cache for later identification of the user.

Blockchain validation is provided by receiving a first validation request of a blockchain. A hashing algorithm is applied to a first block of the blockchain to generate a first hash value. In response to the first validation request of the blockchain, a first image from a plurality of images is provided on a display device. The first image is selected to be provided for display on the display device based on the first hash value. The first image may be compared to a second image that was provided for display on the display device prior to the first validation request and that image was provided based on a second hash value to determine whether the first image and the second image are substantially similar, which indicates that no changes have been made to the data in the blockchain.

Blockchain validation is provided by receiving a first validation request of a blockchain. A hashing algorithm is applied to a first block of the blockchain to generate a first hash value. In response to the first validation request of the blockchain, a first image from a plurality of images is provided on a display device. The first image is selected to be provided for display on the display device based on the first hash value. The first image may be compared to a second image that was provided for display on the display device prior to the first validation request and that image was provided based on a second hash value to determine whether the first image and the second image are substantially similar, which indicates that no changes have been made to the data in the blockchain.

The present invention provides an information processing apparatus and a method of controlling the same. The information processing apparatus has a console unit that accepts an instruction by a user via a button displayed on a screen. The information processing apparatus registers a setting for executing processing corresponding to the button, prompts a user to input identification information to be added to image data generated by a function corresponding to the button, and when the button is instructed via the console unit, the information processing apparatus outputs the image data to which the identification information has been added to a destination corresponding to the setting which is registered in association with the button.

Various embodiments of the present disclosure relate generally to systems and methods for automatic tagging of objects on a multi-view interactive digital media representation of a dynamic entity. According to particular embodiments, the spatial relationship between multiple images and video is analyzed together with location information data, for purposes of creating a representation referred to herein as a multi-view interactive digital media representation for presentation on a device. Multi-view interactive digital media representations correspond to multi-view interactive digital media representations of the dynamic objects in backgrounds. A first multi-view interactive digital media representation of a dynamic object is obtained. Next, the dynamic object is tagged. Then, a second multi-view interactive digital media representation of the dynamic object is generated. Finally, the dynamic object in the second multi-view interactive digital media representation is automatically identified and tagged.

A digital work may be annotated using an eBook reader device. Upon receiving an annotation relating to a specific portion of the digital work, an invariant location reference identifier corresponding to the specified portion of the digital work may be appended to the annotation. The annotation may then be stored in association with the digital work for later reference. In some instances, an annotation may be presented on an eBook reader device upon receipt of a valid authorization credential granting access to the annotation.

A digital work may be annotated using an eBook reader device. Upon receiving an annotation relating to a specific portion of the digital work, an invariant location reference identifier corresponding to the specified portion of the digital work may be appended to the annotation. The annotation may then be stored in association with the digital work for later reference. In some instances, an annotation may be presented on an eBook reader device upon receipt of a valid authorization credential granting access to the annotation.

Embodiments of this application disclose a method for retrieving similar videos performed at a computing device. The computing device obtains video information of a video for which similar videos are to be retrieved, the video information including a video tag and a video title, and trains the video information by using a preset text depth representation model, to convert the video information into a word vector. After selecting, from a video library according to a preset knowledge graph, videos matching the video information, to obtain a first candidate video set, the computing device screens, in the video library, videos similar to the video information according to the word vector, to obtain a second candidate video set and then determines a similar video for the video information from the first candidate video set and the second candidate video set.

A machine may be configured to execute a machine-learning process for identifying and understanding fine properties of various items of various types by using images and associated corresponding annotations, such as titles, captions, tags, keywords, or other textual information applied to these images. By use of a machine-learning process, the machine may perform property identification accurately and without human intervention. These item properties may be used as annotations for other images that have similar features. Accordingly, the machine may answer user-submitted questions, such as What do rustic items look like?, and items or images depicting items that are deemed to be rustic can be readily identified, classified, ranked, or any suitable combination thereof.