A system determines spatial locations of pixels of an image. The system includes a processor configured to: receive location data from devices located within a hotspot; generate a density map for the hotspot including density pixels associated with spatial locations defined by the location data, each density pixel having a value indicating an amount of location data received from an associated spatial location; match the density pixels of the density map to at least a portion of the pixels of the image; and determine spatial locations of the at least a portion of the pixels of the image based on the spatial locations of the matching density pixels of the density map. In some embodiments, the image and density map are converted to edge maps, and a convolution is applied to the edge maps to match the density map to the pixels of the image.

Arrangement for acquiring images for producing a head related transfer function filter is disclosed. In the arrangement the camera of a mobile phone or similar portable device is adjusted for the imaging. All acquired images are analyzed and only suitable images are sent further for producing the head related transfer filter. The arrangement is further configured to provide instructions to the user so that the whole head and other relevant body parts are sufficiently covered.

A method includes: accessing a floorplan representing the floorspace; and extracting from the floorplan a set of floorplan features representing areas of interest in the floorspace. The method also includes, calculating a set of target locations relative to the floorplan that, when occupied by the set of sensor blocks: locate the areas of interest in the floorspace within fields of view of the set sensor blocks; and yield a minimum overlap in fields of view of adjacent sensor blocks in the set of sensor blocks. The method further includes, for each sensor block in the sensor blocks installed over the floorspace: receiving, from the sensor block, an image of the floorspace; based on overlaps in the image with images from other sensor blocks in sensor blocks, estimating an installed location of the sensor block; and mapping the sensor block to a target location in the set of target locations.

A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

A mammography apparatus includes a diagnostic image acquisition unit that acquires a diagnostic image in which a calcification as a biopsy target is marked; a scout image acquisition unit that acquires a scout image obtained by imaging a mamma undergoing the biopsy from a specific direction; and a display unit that highlights a calcification (candidate for biological tissue examination) in the scout image which matches at least the marked calcification in the diagnostic image.

A non-transitory computer-readable recording medium stores therein an extraction program that causes a computer to execute a process including: generating a plurality of combinations of conditions relating to a plurality of item values included in data; calculating an index value that indicates a degree of cooccurrence between a specified response variable and each of the plurality of combinations, by using a machine learning model that estimates a response variable from the plurality of item values, the machine learning model having been trained by using the data; and extracting a specific combination from among the plurality of combinations based on any one of the condition and the index value.

An image detection method determines a target object. A plurality of original images of a scene in front of a vehicle are obtained. An object in one original image is detected, and a degree of similarity between the object in the original image and the target object in a preset image is calculated. If the degree of similarity is greater than a preset similarity threshold, it is determined that the original image is a target image and the object is the target object. A position of the target object relative to the vehicle is determined and output. The method can recognize objects of interest in front of a driver.

A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute a process including: extracting a first feature from an image; detecting, from the extracted first feature, a plurality of visual entities included in the image; generating a second feature in which the visual entities in at least one combination of the plurality of detected visual entities are combined, in first feature, with each other; generating, based on the first feature and the second feature, a first map that indicates relation of each visual entity; extracting a fourth feature based on the first map and a third feature obtained by converting the first feature; and estimating the relation from the fourth feature.

The present invention discloses a method of detecting an abusing act in an online service, the method including: a use act information collecting operation in which an apparatus for detecting an abusing act collects use act information including the kinds and an order of one or more use acts performed by a user; an image configuring operation in which the kinds of the one or more use acts performed by the user are arranged in a time order and an image is configured by setting the kinds of predetermined use acts to a first axis and setting the order of the use acts to a second axis; and an abusing act detecting operation in which whether the use act of the user is an abusing act is detected by using the image.