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.

A method and a computing device for integrating digital content into a database by, in some embodiments, segmenting the digital content into at least one region, sampling the at least one region of the digital content, and selecting the at least one region of the digital content, based on the sampling. In some embodiments, the method may include, and computing device may perform, quantizing the digital content into at least one fragment, based at least on the selecting, compressing the at least one quantized fragment into at least one pHash, and selecting and storing the at least one pHash. In some examples, the storing may be on a blockchain. In some examples, the at least one region may be distinct from the at least one fragment.

A method and a computing device for integrating digital content into a database by, in some embodiments, segmenting the digital content into at least one region, sampling the at least one region of the digital content, and selecting the at least one region of the digital content, based on the sampling. In some embodiments, the method may include, and computing device may perform, quantizing the digital content into at least one fragment, based at least on the selecting, compressing the at least one quantized fragment into at least one pHash, and selecting and storing the at least one pHash. In some examples, the storing may be on a blockchain. In some examples, the at least one region may be distinct from the at least one fragment.

Digital image data including discrete photographic images of a variety of different subjects, times, and so forth, are collected and analyzed to identify specific features in the photographs. In an embodiment of the invention, distinctive markers are distributed to aid in the identification of particular subject matter. Facial recognition may also be employed. The digital image data is maintained in a database and quarried in response to search requests. The search requests include criteria specifying any feature category or other identifying information, such as date, time, and location that each photograph was taken, associated with each photograph. Candidate images are provided for review by requesters, who may select desired images for purchase or downloading.

Digital image data including discrete photographic images of a variety of different subjects, times, and so forth, are collected and analyzed to identify specific features in the photographs. In an embodiment of the invention, distinctive markers are distributed to aid in the identification of particular subject matter. Facial recognition may also be employed. The digital image data is maintained in a database and quarried in response to search requests. The search requests include criteria specifying any feature category or other identifying information, such as date, time, and location that each photograph was taken, associated with each photograph. Candidate images are provided for review by requesters, who may select desired images for purchase or downloading.

A method may include receiving image data representative of cash acquired via one or more image sensors, identifying a first currency depicted in the cash based on a plurality of images associated with a plurality of currencies, and determining a currency conversion rate between the first currency and a second currency. The method may also include generating a visualization representative of a currency value of the cash in the second currency based on the currency conversion rate and overlaying the visualization on the image data.

A method may include receiving image data representative of cash acquired via one or more image sensors, identifying a first currency depicted in the cash based on a plurality of images associated with a plurality of currencies, and determining a currency conversion rate between the first currency and a second currency. The method may also include generating a visualization representative of a currency value of the cash in the second currency based on the currency conversion rate and overlaying the visualization on the image data.

In some examples, a database system includes a memory to store a predicate-object name cache, where the predicate-object name cache contains predicates mapped to respective object names. The database system further includes at least one processor to receive a query containing a given predicate, identify, based on accessing the predicate-object name cache, one or more object names indicated by the predicate-object name cache as being relevant for the given predicate, retrieve one or more objects identified by the one or more object names from a remote data store, and process the query with respect to data records of the one or more objects retrieved from the remote data store.

A computer-implemented consultation assistant assists in the planning and documenting of aesthetic medical procedures. A modification suggestion component automatically suggests modifications and aesthetic procedures to the patient based on reference imagery of a desired outcome, enabling a patient to explain the outcome they want by using visual references. Also included is an imagery guidance component that instructs a user to record standardised imagery of the patient before the procedure and on one or more occasions after the procedure has been performed. The imagery is automatically aligned in space and video is automatically aligned in time, with colour correction and other processing techniques, to enable a true assessment of the results of the procedure.

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.