Abstract: A processing apparatus includes at least one processor configured to function as: an input unit that receives encrypted data based on homomorphic encryption as an input; and a process execution unit that executes a predetermined process by using the encrypted data while maintaining a secret state by encryption and includes one or more processing units. At least one of the processing units is a multiplication corresponding processing unit for executing a calculation in a ciphertext space corresponding to a processing of multiplying plaintext data by a predetermined multiplier. The multiplication corresponding processing unit executes a calculation in the ciphertext space corresponding to a calculation of multiplying the plaintext data by an adjustment multiplication value on first encrypted data input from a preceding stage and outputs resulting data.

Abstract: To achieve efficient reading of data from a memory including a plurality of banks by specifying different banks and accessing the memory from a plurality of hash computation circuits simultaneously, an information processing device includes a memory 1 including a plurality of banks, a plurality of hash computation circuits 8, and an interconnect 2 respectively connecting the banks in the memory 1 and the hash computation circuits 8 to each other, wherein the hash computation circuits 8 execute control in such a manner that read requests for reading data from the memory 1 respectively include bank numbers for specifying different banks in the same cycle.

Abstract: Provided is an image data processing method for preventing decrease of a decoding processing capability of an image processing device even if the image processing device is included in a game machine on which many moving pictures having low resolutions are displayed. First, decoding processing is designed (step S1). For example, it is designed in such a manner that a moving picture X is singly processed and that a moving picture Y and a moving picture Z having low vertical resolutions can be combined together to be subjected to decoding processing. Subsequently, each of the moving picture X, the moving picture Y, and the moving picture Z is encoded (step S2). Next, encoded data of the moving picture X is singly decoded, and the moving picture X is restored and displayed on a display unit of the image processing device at a predetermined timing.

Abstract: An encryption processing system includes: an encryption data generation device, an encryption processing device, and a processing result utilization device. A first processor of the encryption data generation device is configured to perform preprocessing by generating encrypted data of homomorphic encryption corresponding to data obtained by multiplying plaintext data as a target by a power of a predetermined number of two or more. A second processor of the encryption processing device is configured to perform acquiring the encrypted data, and executing a processing on the encrypted data in an encrypted state to obtain a processing result in the encrypted state. A third processor of the processing result utilization device is configured to perform acquiring the processing result, and postprocessing by decrypting data of the processing result in the encrypted state and by dividing the decrypted data by the power of the predetermined number of two or more.

Abstract: A server apparatus transmits information including a hash value of a previous block, data of a current block, and a search range with regard to one blockchain system to a client apparatus in a mining pool. The client apparatus calculates a Nonce value based on the information transmitted from the server apparatus and transmits the calculated Nonce value to the server apparatus. The server apparatus can transmit information regarding a plurality of blockchain systems to the client apparatus. The server apparatus decides one blockchain system based on a predetermined condition, transmits information related to the decided blockchain system to the client apparatus, and causes the client apparatus to perform mining.

Abstract: To provide a processing device, a processing method, a computer program, and a processing system that improve efficiency of an arithmetic processing by using a convolutional neural network (CNN). The processing device inputs data to a convolutional neural network including a convolutional layer and acquires an output from the convolutional neural network. The processing device includes a first converter that performs non-linear space conversion on data to be input to the convolutional neural network, and/or a second converter that performs non-linear space conversion on data output from the convolutional neural network.

Abstract: To provide a computer program, an image processing method, and an image processing apparatus that avoid deterioration due to free deformation with respect to a digital image. The computer program causes a computer to execute a process of receiving editing order including scaling, rotation, shifting, or distortion with respect to a digital image to be processed, identifying a target resolution of the digital image to be processed, generating a temporary reference image with a resolution predetermined times the target resolution based on the digital image, performing rotation, shifting, or distortion in the received editing with respect to the temporary reference image, and outputting the digital image with the target resolution by performing sampling at a rate corresponding to the target resolution with respect to the edited temporary reference image.

Abstract: To provide a processing device, a processing method, a computer program, and a processing system that improve efficiency of an arithmetic processing by using a convolutional neural network (CNN). The processing device inputs data to a convolutional neural network including a convolutional layer and acquires an output from the convolutional neural network. The processing device includes a first converter that performs non-linear space conversion on data to be input to the convolutional neural network, and/or a second converter that performs non-linear space conversion on data output from the convolutional neural network.

Abstract: To provide a learning apparatus and an inferring apparatus that can prevent problems such that a computation amount increases, efficiency of a learning process decreases, and an inferring result does not have high accuracy. A learning apparatus and an inferring apparatus include a predictable area determining unit that determines whether target data has a predictable area in which an inferring result of an inferring process can be easily predicted. In the learning apparatus and the inferring apparatus, predetermined data processing is performed on a data area that is determined to be a predictable area, data required to infer an area that is not a predictable area is output to a machine learning model, and data processing is performed in an average time shorter than that of the inferring process.

Abstract: An aspect of the invention is directed to an imaging module including: an imaging device which converts an input optical image into image data; an encryption device which encrypts the image data by a homomorphic encryption method; and an interface which outputs encrypted image data received from the encryption device.

Abstract: A trading system includes a first trading apparatus including a first processor, and a second trading apparatus including a second processor. The first processor encrypts data using secret information. The first processor publishes second trading information on a distributed ledger when first trading information enabling reception of crypto assets on a condition of publication of argument information that enables derivation of the secret information is published on a distributed ledger. The second trading information is information for receiving the crypto assets and includes the argument information. The second processor publishes the first trading information on a distributed ledger. The second processor acquires the argument information when the second trading information is published on a distributed ledger. The second processor decrypts encrypted data using the argument information.

Abstract: An inference system includes a first device and a second device. The first device includes a first processor which executes the following processing. The first processor loads a learned model created by the second device, including first control information for causing the first device to perform postprocessing. The first processor accepts input of input data of a neural network, which is an object of an inference process. The first processor executes the inference process on the input data by using the learned model. The first processor performs the postprocessing that converts a data format of output data output as a result of the inference process to a format corresponding to subsequent processing in accordance with the first control information included in the learned model. The second device includes a second processor which performs the following processing. The second processor creates the learned model including the first control information.

Abstract: To provide a technique of preventing leakage of a network structure and a weight included in a learned model. An inference apparatus includes a determination unit, a decryption unit, and an inference unit. The determination unit determines whether encrypted learned model, in which a learned model including at least one of the structure and the weight of a neural network is encrypted, has been input. The decryption unit decrypts the encrypted learned model, when the encrypted learned model is input. The inference unit performs inference by using the decrypted learned model.

Abstract: Provided is an image data processing method. First, decoding processing designed (step S1) in such a manner that a moving picture X is singly processed and that a moving picture Y and Z having low vertical resolutions can be combined together to be subjected to decoding processing. Subsequently, each of the moving picture X, Y, and Z is encoded (step S2). Next, encoded data of the moving picture X is singly decoded, and the moving picture X is restored and displayed on a display unit of the image processing device at a predetermined timing. Meanwhile, respective pieces of encoded data of the moving picture Y and Z are combined together and are decoded depending on respective display timings, and the moving picture X and Y are restored and further separated from each other to be displayed on the display unit at the respective timings (step S3).

Abstract: A server apparatus transmits information including a hash value of a previous block, data of a current block, and a search range with regard to one blockchain system to a client apparatus in a mining pool. The client apparatus calculates a Nonce value based on the information transmitted from the server apparatus and transmits the calculated Nonce value to the server apparatus. The server apparatus can transmit information regarding a plurality of blockchain systems to the client apparatus. The server apparatus decides one blockchain system based on a predetermined condition, transmits information related to the decided blockchain system to the client apparatus, and causes the client apparatus to perform mining.

Abstract: A unit that divides an image into a mesh shape and acquires depth information and an X-coordinate and a Y-coordinate for vertices of each grid, a unit that transforms vertex data into three-dimensional space coordinates expressed by a predetermined coordinate system, a unit that calculates line segment vectors and a normal vector that constitute each grid based on the three-dimensional space coordinates of each vertex, a vector management part that assigns indexes for distinguishing unique vectors from each other to the respective unique vectors, and generates a vector list in which the unique vectors and the indexes are respectively associated with each other, and a unit that stores therein indexes of the vectors that constitute each grid, while being associated with the grid.

Abstract: A learning apparatus that learns a set value in a machine learning model based on predetermined image data for learning includes an inverting unit that inverts data of at least a part of respective channels in the image data for learning, an input unit that inputs the inverted data to the machine learning model, an output unit that can compare data obtained by inverting data output from the machine learning model with training data, and/or data output from the machine learning model with data obtained by inverting training data, and a learning process executing unit that learns the set value according to a result of the comparison.

Abstract: A learning method, a learning model, a classifier, a generator, and a processing system are provided, which consider human vision in learning using a machine learning model for an image. The learning method learns a machine learning model that inputs or outputs image data with data for learning that includes both or either one of image data in which a component that is difficult to judge visually is left out and image data in which a noise component that is difficult to judge visually is added at a predetermined ratio.

Abstract: An encryption processing system includes: an encryption data generation device, an encryption processing device, and a processing result utilization device. A first processor of the encryption data generation device is configured to perform preprocessing by generating encrypted data of homomorphic encryption corresponding to data obtained by multiplying plaintext data as a target by a power of a predetermined number of two or more. A second processor of the encryption processing device is configured to perform acquiring the encrypted data, and executing a processing on the encrypted data in an encrypted state to obtain a processing result in the encrypted state. A third processor of the processing result utilization device is configured to perform acquiring the processing result, and postprocessing by decrypting data of the processing result in the encrypted state and by dividing the decrypted data by the power of the predetermined number of two or more.

Abstract: To provide a display processing device that displays the structure of a displayed item configured by stacking a plurality of displayed items in an understandable manner and enables easy confirmation of each of the layers being stacked and displayed. The display processing device includes a graduation-image display unit (a graduation-display processing unit) 24 causing a display device 15 to display a graduation image having values the number of which corresponds to the number of a plurality of image layers, a specification unit (a pointer-display processing unit) 25 causing a value on the graduation image to be specified, and a displayed-number determination unit (a number-of-displayed-layers determination processing unit) 26 determining the number of image layers that are to be stacked and displayed by the display device 15, among the plurality of image layers in accordance with the value on the graduation image specified by the specification unit 25.