A method for making texture symbols of a land use classification map is disclosed in the disclosure, including: capture of texture materials; extraction of main colors; color clustering; extraction of a texture skeleton; tile effect removal; and establishment of a texture library. The disclosure has the following advantages: definitions and classes of texture symbols are provided, and a procedure of making texture symbols is made clear; used natural texture symbols and symbolic texture symbols have clear semantic meanings, facilitating information transfer of the map; the quality and layering of the map are improved; the texture symbols can be directly used for production, to provide a fundamental support for survey and mapping of land use, and also to provide a solution for large-scale result mapping of natural resource survey. The expression of thematic maps of current land use classification is improved.

A process for locating real estate parcels for a user comprises accessing a library of parceled real estate image data to identify objects and features in a plurality of parcels identified by the user as having a feature of interest. A predictive model is constructed and applied to a geographic region selected by the user to generate a customized output of real estate parcels predicted to have the feature of interest.

The present disclosure discloses an image processing method, apparatus, and a non-transitory computer readable medium. The method can includes: acquiring a three-dimensional (3D) model and original texture images of an object, wherein the original texture images are acquired by an imaging device; determining a mapping relationship between the 3D model and the original texture images of the object; determining, among the original texture images, a subset of texture images associated with a first perspective of the imaging device; splicing the subset of texture images into a spliced texture image corresponding to the first perspective; and mapping the spliced texture image to the 3D model according to the mapping relationship.

The Loupe system creates a display and channel creation capability for art images to be presented to a user to optimize the user experience in viewing art images delivered onto digital displays, TVs and other screens facilitating the artwork transition with and without human interaction. Art imagery to be streamed includes imagery such as, but not limited to, filtered and personalized streams of art imagery. The Loupe system recommendations engine utilizes both human and machine curated data to determine factors of art images that optimize and extend the user time spent on viewing the images. The Loupe system gathers data that is analyzed through machine learning and AI algorithms to inform recommendations and select art images to optimize the user experience. The user may purchase fine art prints or select originals of the artwork image displayed, if available for sale, from the Loupe integrated electronic marketplace.

The Loupe system defines Loupe Visual Art DNA for art images to be presented to a user so as to maximize and customize the user experience in viewing art images delivered onto digital displays, TVs and other screens facilitating the artwork transition with and without human interaction. The Loupe system recommendations engine utilizes both human and machine curated data to determine factors of art images that will appeal to a user viewing the images. The Loupe system gathers data about visual perception, historical and academic provenance, and emotion or intention represented in an image. The gathered data is analyzed through deep learning and Al algorithms to inform recommendations and select art images to be presented to a user. The user may purchase fine art prints or select originals of the artwork image displayed, if the artist elects to make it available for sale, presented from the Loupe integrated electronic marketplace.

Methods and systems for automatically creating item records for physical items. The method may include receiving an image obtained using an image sensor; detecting a physical item in the image; extracting item data regarding the physical item by applying image analysis to the image; determining, using the extracted item data, whether a memory contains an item record for the physical item; and, when no item record for the physical item exists in the memory, generating and storing in the memory a new item record for the physical item in association with the extracted item data

The Loupe system defines Loupe Visual Art DNA for art images to be presented to a user so as to maximize and customize the user experience in viewing art images delivered onto digital displays, TVs and other screens facilitating the artwork transition with and without human interaction. The Loupe system recommendations engine utilizes both human and machine curated data to determine factors of art images that will appeal to a user viewing the images. The Loupe system gathers data about visual perception, historical and academic provenance, and emotion or intention represented in an image. The gathered data is analyzed through deep learning and Al algorithms to inform recommendations and select art images to be presented to a user. The user may purchase fine art prints or select originals of the artwork image displayed, if the artist elects to make it available for sale, presented from the Loupe integrated electronic marketplace.

Embodiments of the present disclosure provide systems, methods, and computer storage media for optimizing computing resources generally associated with cloud-based media services. Instead of decoding digital assets on-premises to stream to a remote client device, an encoded asset can be streamed to the remote client device. A codebook employable for decoding the encoded asset can be embedded into the stream transmitted to the remote client device, so that the remote client device can extract the embedded codebook, and employ the extracted codebook to decode the encoded asset locally. In this way, not only are processing resources associated with on-premises decoding eliminated, but on-premises storage of codebooks can be significantly reduced, while expensive bandwidth is freed up by virtue of transmitting a smaller quantity of data from the cloud to the remote client device.

Kinship between electronic files among personal networked devices may be ascertained between the files by determining an operational relationship between the files and with a similarity measurement.

Embodiments of the present disclosure provide systems, methods, and computer storage media for optimizing computing resources generally associated with cloud-based media services. Instead of decoding digital assets on-premises to stream to a remote client device, an encoded asset can be streamed to the remote client device. A codebook employable for decoding the encoded asset can be embedded into the stream transmitted to the remote client device, so that the remote client device can extract the embedded codebook, and employ the extracted codebook to decode the encoded asset locally. In this way, not only are processing resources associated with on-premises decoding eliminated, but on-premises storage of codebooks can be significantly reduced, while expensive bandwidth is freed up by virtue of transmitting a smaller quantity of data from the cloud to the remote client device.