Abstract: A learning device comprises: an acquisition unit that acquires a first feature amount derived by an encoder from data with an identification object recorded therein, the encoder being configured so as to derive, from data with the identical object in various forms recorded therein, feature amounts which are mutually convertible by a conversion using a conversion parameter that takes a value according to the difference in the forms; a conversion unit that generates a second feature amount by performing a conversion on the first feature amount using the conversion parameter value; and a parameter updating unit that updates the value of a sorting parameter used in sorting by a sorting means, which is configured to sort second feature amounts as input, such that if the second feature amount has been input, the sorting means outputs a result indicating, as a sorting destination, a class associated with the identification object.

Abstract: An arrival time acquisition unit acquires a time at which a user has arrived at an airport. A length of stay information generation unit calculates a length of stay based on the time at which the user has arrived and a scheduled boarding time of an aircraft on which the user is scheduled to board and generates length of stay information including the length of stay. A behavioral characteristic estimation unit estimates a behavioral characteristic of the user based on the generated length of stay information and a behavioral characteristic table. A benefit determination unit refers to a benefit information table and determines benefit information to be distributed to the user based on the estimated behavioral characteristic. A benefit transmission unit transmits the determined benefit information to a terminal apparatus carried by the user.

Abstract: An identification device according to one embodiment comprises: an acquisition unit that uses an encoder configured to derive, from data in which a single subject under different conditions has been recorded, feature values as a first feature value derived from data in which a subject to be identified has been recorded; a conversion unit that generates a second feature value by carrying out conversion using the conversion parameter on the first feature value; a discrete classification unit that carries out discrete classification on each of a plurality of third feature values including the second feature value and generates a plurality of discrete classification results indicating the results of the classification; a result derivation unit that derives, on the basis of the plurality of discrete classification results, identification result information; and an output unit that outputs the identification result information.

Abstract: A wave-source-direction estimation device includes: input units that acquire, as input signals, electrical signals that have been converted from waves acquired by sensors; a signal selection unit that selects at least two pairs that are each a combination of at least two input signals from among the input signals; a relative delay time calculation unit that calculates, as relative delay times, arrival time differences of the waves for each wave source searching direction between the at least two input signals composing one of the pairs of the input signals; at least one per-frequency estimated-direction-information generation unit that uses the pairs of the input signals and the relative delay times to generate estimated direction information on a wave source of the waves for each frequency; and an integration unit that integrates the estimated direction information generated for each frequency by the per-frequency estimated-direction-information generation unit.

Abstract: A wave-source-direction estimation device includes: a plurality of input units that acquires, as input signals, electrical signals based on waves detected by a plurality of sensors; a signal selection unit that selects a plurality of pairs that are each a combination of two input signals from among a plurality of the input signals; a relative delay time calculation unit that calculates, as relative delay times, arrival time differences of the waves at the sensors that are supply sources of the two input signals composing each of the pairs, for each wave source direction; and an integrated-estimated-direction-information calculation unit that generates per-frequency estimated direction information for each of the pairs using the input signals composing each of the pairs and the relative delay times of each of the pairs and generates integrated estimated direction information by assigning a weight to and integrating the estimated direction information on all the pairs.

Abstract: A radar signal imaging device 30 includes: a transmission unit 31 which transmits a radar signal toward an object to be imaged that is a non-rigid body; a position estimation unit 32 which estimates the position of the object; an oscillation degree estimation unit 33 which estimates an oscillation degree which is a degree of change within a predetermined period in the relative positions of feature points constituting the object; and a synthetic aperture processing unit 34 which performs synthetic aperture processing on the radar signal reflected by the object on the basis of the estimated position of the object and the estimated oscillation degree.

Abstract: An identification device according to one embodiment comprises: an acquisition unit that uses an encoder configured to derive, from data in which a single subject under different conditions has been recorded, feature values as a first feature value derived from data in which a subject to be identified has been recorded; a conversion unit that generates a second feature value by carrying out conversion using the conversion parameter on the first feature value; a discrete classification unit that carries out discrete classification on each of a plurality of third feature values including the second feature value and generates a plurality of discrete classification results indicating the results of the classification; a result derivation unit that derives, on the basis of the plurality of discrete classification results, identification result information; and an output unit that outputs the identification result information.

Abstract: Provided is a processing device capable of, on the basis of data prepared by a recorder that only has recording function, acquiring information related to a time when the data was prepared. The processing device includes an acquisition unit for acquiring the recorded audio data, and an identification unit for detecting a sound signal that is included in the audio data and transmitted from an information transmission device and allows the time at which the signal was recorded to be identified, and identifying the time when other signals included in the audio data were recorded on the basis of the sound signal.

Abstract: A learning device comprises: an acquisition unit that acquires a first feature amount derived by an encoder from data with an identification object recorded therein, the encoder being configured so as to derive, from data with the identical object in various forms recorded therein, feature amounts which are mutually convertible by a conversion using a conversion parameter that takes a value according to the difference in the forms; a conversion unit that generates a second feature amount by performing a conversion on the first feature amount using the conversion parameter value; and a parameter updating unit that updates the value of a sorting parameter used in sorting by a sorting means, which is configured to sort second feature amounts as input, such that if the second feature amount has been input, the sorting means outputs a result indicating, as a sorting destination, a class associated with the identification object.

Abstract: Provided is a learning device that can generate a feature deriving device capable of deriving, for an identical object, feature amounts which respectively express a feature of the object in different forms and which are mutually related. This learning device comprises: an acquisition unit that acquires first data and second data, with different forms of the object recorded therein; an encoder that derives a first feature amount from the first data; a conversion unit that converts the first feature amount to a second feature amount; a decoder that generates third data from the second feature amount; and a parameter updating unit that updates, on the basis of a comparison between the second data and the third data, the value of a parameter used in the derivation of the first feature amount, and the value of a parameter used in the generation of the third data.

Abstract: An object is to provide an image processing apparatus capable of appropriately distinguishing various object types. An image processing apparatus (1C) comprising: detector means (11) for detecting objects in an input SAR image and generating object chips; projection calculator means (12) for calculating projection information of each object using SAR geometry; feature learner means (14) for learning, for each object, a relation between an object chip and its projection information, and thereby generating learnt features of object chips; and classifier means (15) for classifying object chips into classes based on the learnt features of object chips.

Abstract: A label feature extraction means 71 extracts, from reference information, a label feature that is a vector representing a feature of the reference information. A label feature dimension reduction means 72 performs dimension reduction of the label feature. An image feature extraction means 73 extracts an image feature from a target image that is an image in which an object to be recognized is captured. A feature transformation means 74 performs feature transformation on the image feature in such a manner that comparison with the label feature after the dimension reduction becomes possible. The class recognition means 75 recognizes a class of the object to be recognized by comparing the image feature after the feature transformation with the label feature after the dimension reduction.

Abstract: A video encoding device for encoding video using inter prediction includes encoding control means 11 for controlling an inter-PU partition type of a CU to be encoded, based on a minimum inter-PU size (PA) and a CU size (PB) of the CU to be encoded. A video decoding device includes decoding control means for controlling an inter-PU partition of a CU to be decoded, based on the minimum inter-PU size (PA) and the size (PB) of the CU to be decoded.

Abstract: A video encoding device includes encoding control means 11 for controlling an inter-PU partition type of a CU to be encoded, based on the maximum number (PA) of motion vectors allowed for an image block having a predetermined area and the number (PB) of motion vectors of an encoded image block contained in the image block having the predetermined area. A video decoding device includes decoding control means for controlling an inter-PU partition type of a CU to be decoded, based on the maximum number (PA) of motion vectors allowed for an image block having a predetermined area and the number (PB) of motion vectors of a decoded image block contained in the image block having the predetermined area.

Abstract: A signal source identification device includes: a feature value calculation unit configured to calculate feature values corresponding to paths where signals from generation sources of the signals transmit, based on signals received by a plurality of sensors; and an identification unit configured to identify whether or not a feature value calculated by the feature value calculation unit is a signal from a predetermined signal source by using an identification range that is a range within which feature values based on signals from the predetermined signal source fall and that is previously determined based on the feature values calculated by the feature value calculation unit.

Abstract: In a video decoding device, a quantization step size decoding unit calculates a quantization step size that controls a granularity of the inverse quantization by, based on an image prediction, selectively using a mean value of at least a quantization step size assigned to a leftwardly adjacent neighboring image block already decoded and a quantization step size assigned to a upwardly adjacent neighboring image block already decoded or a quantization step size assigned to an image block decoded immediately before.

Abstract: In a video decoding device, a quantization step size decoding unit calculates a quantization step size that controls a granularity of the inverse quantization by, based on an image prediction, selectively using a mean value of at least a quantization step size assigned to a leftwardly adjacent neighboring image block already decoded and a quantization step size assigned to a upwardly adjacent neighboring image block already decoded or a quantization step size assigned to an image block decoded immediately before.

Abstract: In a video decoding device, a quantization step size decoding unit calculates a quantization step size that controls a granularity of the inverse quantization by, based on an image prediction, selectively using a mean value of at least a quantization step size assigned to a leftwardly adjacent neighboring image block already decoded and a quantization step size assigned to a upwardly adjacent neighboring image block already decoded or a quantization step size assigned to an image block decoded immediately before.

Abstract: A video encoding device for encoding video using inter prediction includes encoding control means 11 for controlling an inter-PU partition type of a CU to be encoded, based on a minimum inter-PU size (PA) and a CU size (PB) of the CU to be encoded. A video decoding device includes decoding control means for controlling an inter-PU partition of a CU to be decoded, based on the minimum inter-PU size (PA) and the size (PB) of the CU to be decoded.

Abstract: A video encoding device includes encoding control means 11 for controlling an inter-PU partition type of a CU to be encoded, based on the maximum number (PA) of motion vectors allowed for an image block having a predetermined area and the number (PB) of motion vectors of an encoded image block contained in the image block having the predetermined area. A video decoding device includes decoding control means for controlling an inter-PU partition type of a CU to be decoded, based on the maximum number (PA) of motion vectors allowed for an image block having a predetermined area and the number (PB) of motion vectors of a decoded image block contained in the image block having the predetermined area.