Abstract: A storage device includes a memory cell that includes a variable resistance storage element and a switching element connected in series thereto and stacked therewith in a first direction, the switching element including a first electrode, a second electrode that includes a first part formed of a first material to which a first element is added, and a switching material layer that is between the first electrode and the first part of the second electrode and formed of a first insulating material to which the first element is added. The storage device further includes a first insulating layer that surrounds the switching material layer and formed of the first insulating material to which the first element is not added. An outer periphery of the first part of the second electrode and an outer periphery of the switching material layer are aligned in the first direction.

Abstract: A display control system for displaying a GUI screen on a terminal of a user, the display control system includes: a setting GUI unit, wherein the setting GUI unit is configured to cause the terminal to display a screen depicting a network configuration including a plurality of selectable clouds, and wherein the setting GUI unit is configured to cause the terminal to display a parameter input screen for a connection between a specific cloud and a resource in a case where the specific cloud and the resource to connect to the specific cloud are selected at the terminal.

Abstract: A display control system for displaying a GUI screen on a terminal of a user, the display control system includes: a setting GUI unit, wherein the setting GUI unit is configured to cause the terminal to display a screen depicting a network configuration including a plurality of selectable clouds, and wherein the setting GUI unit is configured to cause the terminal to display a parameter input screen for a connection between a specific cloud and a resource in a case where the specific cloud and the resource to connect to the specific cloud are selected at the terminal.

Abstract: According to an embodiment, a data management system includes an index building unit and a searching unit. The index building unit generates a peripheral vector similar to a case example vector representing a feature vector of data to be stored, and builds index information of enabling identification of the case example vector corresponding to the generated peripheral vector. The searching unit refers to the index information in response to a search request in which a query vector representing an arbitrary feature vector is specified, identifies the case example vector corresponding to the peripheral vector that exactly matches with the query vector, and outputs a search result based on the identified case example vector.

Abstract: In an image processing system, an image processing apparatus configured to recognize images of documents is connected through a network to terminal apparatuses each including an input unit and a display unit. The image processing apparatus includes: a recognition unit configured to perform character recognition processing on an image; a confidential information detecting unit configured to detect confidential information from a result of the character recognition processing; and a manipulation unit configured to generate, based on the confidential information in the image, a first manipulated image obtained by fragmenting the confidential information. Each of the terminal apparatuses includes: a display unit configured to display the first manipulated image; and an input unit configured to input corrected data for the first manipulated image.

Abstract: According to an embodiment, a pattern recognition device is configured to divide an input signal into a plurality of elements, convert the divided elements into feature vectors having the same dimensionality to generate a set of feature vectors, and evaluate the set of feature vectors using a recognition dictionary including models corresponding to respective classes, to output a recognition result representing a class or a set of classes to which the input signal belongs. The models each include sub-models each corresponding to one of possible division patterns in which a signal to be classified into a class corresponding to the model can be divided into a plurality of elements. A label expressing a model including a sub-model conforming to the set of feature vectors, or a set of labels expressing a set of models including sub-models conforming to the set of feature vectors is output as the recognition result.

Abstract: According to an embodiment, a pattern recognition device recognizes a pattern of an input signal by converting the input signal to a feature vector and matching the feature vector with a recognition dictionary. The recognition dictionary includes a dictionary subspace basis vector for expressing a dictionary subspace which is a subspace of a space of the feature vector, and a plurality of probability parameters for converting similarity calculated from the feature vector and the dictionary subspace into likelihood. The device includes a recognition unit configured to calculate the similarity using a quadratic polynomial of a value of an inner product of the feature vector and the dictionary subspace basis vector, and calculate the likelihood using the similarity and an exponential function of a linear sum of the probability parameters. The recognition dictionary is trained by using an expectation maximization method using a constraint condition between the probability parameters.

Abstract: According to an embodiment, a data management system includes an index building unit and a searching unit. The index building unit generates a peripheral vector similar to a case example vector representing a feature vector of data to be stored, and builds index information of enabling identification of the case example vector corresponding to the generated peripheral vector. The searching unit refers to the index information in response to a search request in which a query vector representing an arbitrary feature vector is specified, identifies the case example vector corresponding to the peripheral vector that exactly matches with the query vector, and outputs a search result based on the identified case example vector.

Abstract: According to an embodiment, a pattern recognition device recognizes a pattern of an input signal by converting the input signal to a feature vector and matching the feature vector with a recognition dictionary. The recognition dictionary includes a dictionary subspace basis vector for expressing a dictionary subspace which is a subspace of a space of the feature vector, and a plurality of probability parameters for converting similarity calculated from the feature vector and the dictionary subspace into likelihood. The device includes a recognition unit configured to calculate the similarity using a quadratic polynomial of a value of an inner product of the feature vector and the dictionary subspace basis vector, and calculate the likelihood using the similarity and an exponential function of a linear sum of the probability parameters. The recognition dictionary is trained by using an expectation maximization method using a constraint condition between the probability parameters.

Abstract: According to an embodiment, a pattern recognition device is configured to divide an input signal into a plurality of elements, convert the divided elements into feature vectors having the same dimensionality to generate a set of feature vectors, and evaluate the set of feature vectors using a recognition dictionary including models corresponding to respective classes, to output a recognition result representing a class or a set of classes to which the input signal belongs. The models each include sub-models each corresponding to one of possible division patterns in which a signal to be classified into a class corresponding to the model can be divided into a plurality of elements. A label expressing a model including a sub-model conforming to the set of feature vectors, or a set of labels expressing a set of models including sub-models conforming to the set of feature vectors is output as the recognition result.

Abstract: In an image processing system, an image processing apparatus configured to recognize images of documents is connected through a network to terminal apparatuses each including an input unit and a display unit. The image processing apparatus includes: a recognition unit configured to perform character recognition processing on an image; a confidential information detecting unit configured to detect confidential information from a result of the character recognition processing; and a manipulation unit configured to generate, based on the confidential information in the image, a first manipulated image obtained by fragmenting the confidential information. Each of the terminal apparatuses includes: a display unit configured to display the first manipulated image; and an input unit configured to input corrected data for the first manipulated image.

Abstract: According to an embodiment, an information processing device includes a receiving unit, a detection unit, a generation unit, and an output unit. The receiving unit is configured to receive an original image. The detection unit is configured to detect a write region in which additional information is to be written, from the original image. The generation unit is configured to generate a position specifying image for specifying a position of the write region in the original image, the position specifying image being to be added to a predetermined region in the original image. The output unit is configured to output the position specifying image.

Abstract: According to an embodiment, an information processing device includes a receiving unit, a detection unit, a generation unit, and an output unit. The receiving unit is configured to receive an original image. The detection unit is configured to detect a write region in which additional information is to be written, from the original image. The generation unit is configured to generate a position specifying image for specifying a position of the write region in the original image, the position specifying image being to be added to a predetermined region in the original image. The output unit is configured to output the position specifying image.

Abstract: An image recognition apparatus according to one aspect of the present invention has a measurement unit measuring a blur level of an image, a comparison unit comparing the blur level measured in the measurement unit with a threshold, an image processing unit applying to the image a blurring filter which increases the blur level when the blur level measured in the measurement unit is smaller than the threshold, and applying to the image a deblurring filter which decreases the blur level when the blur level measured in the measurement unit is larger than the threshold, and a recognition unit recognizing the image from features of the image processed in the image processing unit.

Abstract: An image recognition apparatus according to one aspect of the present invention has a measurement unit measuring a blur level of an image, a comparison unit comparing the blur level measured in the measurement unit with a threshold, an image processing unit applying to the image a blurring filter which increases the blur level when the blur level measured in the measurement unit is smaller than the threshold, and applying to the image a deblurring filter which decreases the blur level when the blur level measured in the measurement unit is larger than the threshold, and a recognition unit recognizing the image from features of the image processed in the image processing unit.