Abstract: A wire harness routing apparatus includes a case and a wire harness accommodated in the case. An axial portion is provided inside the case, and the wire harness is wound around the axial portion, and the wire harness includes at least one wire and a protective member that protects the wire. The protective member includes an insertion path through which the wire is inserted, and the insertion path is formed between a sheet-shaped base sheet and a sheet-shaped cover sheet that overlaps the base sheet, and the protective member includes joining portions where the base sheet and the cover sheet are joined together at both lateral edges of the insertion path.

Abstract: Provided is a cancer stem cell mass from which cells incapable of forming cancer are substantially removed and which has a characteristic property of reproducing a layered structure of a cancer tissue; a process for producing the cancer stem cell mass; and use of the cancer stem cell mass. A human cancer tissue was repeatedly grown in a NOG mouse, separated cancer cells from the grown cancer tissue, and tested and compared various cancer cell culture processes. As a result, a cancer stem cell composition which is homogeneous and is substantially free of the coexistence of cells capable of forming cancer and cells incapable of forming cancer in a mixed state can be produced successively by employing an attached culture process using a serum-free stem cell culture medium rather than a generally employed floating culture process.

Abstract: An information processing apparatus comprises a processing unit configured to execute, in frame periods corresponding to respective frames, an inference relating to the frame and training relating to the frame. When an inference relating to a first frame has been completed but training relating to the first frame has not been completed in a first frame period corresponding to the first frame, the processing unit executes training relating to the first frame and an inference and training relating to a second frame in a second frame period corresponding to the second frame subsequent to the first frame.

Abstract: An information processing apparatus comprises a conversion unit configured to, if a bit width of a weight coefficient in a first layer in weight coefficients in a plurality of layers is N bits, wherein N is a predetermined integer not less than 2, output the weight coefficient, and if the bit width of the weight coefficient is not N bits, output a weight coefficient of N bits obtained by converting the weight coefficient, and an operation unit configured to generate a feature image in a second layer based on a multiply-accumulate operation between the weight coefficient output by the conversion unit and a feature image in the first layer.

Abstract: There is provided with a processing apparatus. A data holder holds at least some of data of a plurality of channels in a target layer among a plurality of layers. Each of a plurality of processors performs, in parallel, a product-sum operation using the data of one channel of the target layer and a coefficient corresponding to the target layer. A selector selects whether to perform first processing or second processing on the basis of information specifying processing in the target layer. The first processing includes inputting the data of one channel of the target layer into one of the plurality of processors. The second processing includes inputting the data of one channel of the target layer to the plurality of processors in parallel.

Abstract: A data processing apparatus for executing data processing using a neural network including a plurality of hierarchal levels includes an extraction unit configured to extract intermediate feature data from input feature data, a calculation unit configured to calculate output feature data by reducing the number of channels of the intermediate feature data, a storage unit configured to store the output feature data calculated by the calculation unit and provide the input feature data to the extraction unit, and a control unit configured to control the number of channels of the intermediate feature data to be extracted by the extraction unit and the number of channels of the output feature data to be calculated by the calculation unit.

Abstract: There is provided with a filter processing device for performing a convolution operation using a filter on a feature plane. An acquisition unit acquires feature plane data, filter coefficients of the filter, and valid coefficient information which specifies filter coefficients to be used in the convolution operation among the filter coefficients of the filter. A calculation unit performs a convolution operation of the filter coefficients specified by the valid coefficient information and pieces of the feature plane data corresponding to the specified filter coefficients.

Abstract: A data processing apparatus comprises one or more memories storing instructions and one or more processors that, upon execution of the instructions, are configured to sequentially perform processing of data by a plurality of hierarchically connected processing nodes, store, in the one or more memories, processing results of the plurality of respective processing nodes, and processing statuses of and parameters for the plurality of respective processing nodes, the parameters being used determine a processing node to perform the processing, cyclically specify processing nodes, from among the plurality of processing nodes, to perform the processing in an order based on hierarchy, determine whether the processing by a specified processing node is performable based on the stored processing statuses, and determine a processing node to perform the processing based on a result of determination and the stored parameter for the specified processing node.

Abstract: An apparatus sets coefficients in a first array based on first information indicating an image capturing orientation of a first image, generates a first map by applying the coefficients to the first image, acquires a template feature corresponding to an object based on the first map, registers the template feature in an array based on the first information, sets coefficients in a second array based on second information indicating an image capturing orientation of a second image, generates a second map by applying the coefficients set in the second array to the second image, sets the template feature in a feature array based on the second information, performs a correlation calculation between the template feature set in the feature array and the second map, and detects the object from the second image based on a result of the correlation calculation.

Abstract: In order to perform a discrimination calculation using a small-capacity storage unit, a discrimination calculation apparatus comprises a feature calculation unit configured to sequentially calculate a feature of discrimination target data for each hierarchical layer, a discrimination calculation unit configured to sequentially perform a partial discrimination calculation on the discrimination target data using the feature sequentially calculated by the feature calculation unit and store a result of the partial discrimination calculation in a discrimination result storage unit, and a control unit configured to control the discrimination calculation unit to perform a next partial discrimination calculation using the feature sequentially calculated by the feature calculation unit and the result of the partial discrimination calculation stored in the discrimination result storage unit and to store a result of the next partial discrimination calculation in the discrimination result storage unit.

Abstract: To allow arithmetic processing using a plurality of processing nodes to be executed with a smaller memory size, an arithmetic processing apparatus for executing processing using a hierarchical type network formed by the plurality of processing nodes, comprises: a storage unit configured to store a parameter used by each of the plurality of processing nodes for arithmetic processing and a calculation result of the arithmetic processing in each of the plurality of processing nodes; and a buffer control unit configured to switch, based on a configuration of the hierarchical type network, a buffer system of the parameter and the calculation result in the storage unit in at least one layer of the hierarchical type network.

Abstract: An apparatus for performing filter processing on a data array in a processing target block of a predetermined size is provided. A data memory holds the data array in the processing target block. A coefficient memory holds weight coefficients of a filter used for the filter processing. A controller determines, in a determination, whether data in a reference region in the processing target block, set in correspondence with the processing target block, are zero values. A processor generates a convolution operation result of the weight coefficients and data at a plurality of positions in the processing target block. The controller controls, based on a result of the determination, whether to perform at least some of multiply-accumulate operations of the data and the weight coefficients when the processor generates the convolution operation result.

Abstract: An apparatus includes a first holding unit and a second holding unit configured to hold first-type data and second-type data, respectively, a first operation unit configured to execute a first product-sum operation based on the first-type data, a branch unit configured to output an operation result of the first product-sum operation in parallel, a sampling unit configured to sample the operation result and to output a sampling result, and a second operation unit configured to execute a second product-sum operation based on the second-type data and the sampling result.

Abstract: There is provided with a data processing apparatus. An acquisition unit acquires feature plane data of a layer included in a neural network. A control unit outputs a first control signal corresponding to the layer for controlling first compression processing and a second control signal corresponding to the layer for controlling second compression processing. A first compression unit performs the first compression processing corresponding to the first control signal on the feature plane data. A second compression unit performs the second compression processing corresponding to the second control signal on the feature plane data after the first compression processing. A type of processing of the second compression processing is different from the first compression processing.

Abstract: An information processing apparatus operable to perform computation processing in a neural network comprises a coefficient storage unit configured to store filter coefficients of the neural network, a feature storage unit configured to store feature data, a storage control unit configured to store in the coefficient storage unit a part of previously obtained feature data as template feature data, a convolution operation unit configured to compute new feature data by a convolution operation between feature data stored in the feature storage unit and filter coefficients stored in the coefficient storage unit, and compute, by a convolution operation between feature data stored in the feature storage unit and the template feature data stored in the coefficient storage unit, correlation data between the feature data stored in the feature storage unit and the template feature data.

Abstract: An image processing apparatus comprises a first obtaining unit configured to obtain a pixel from a feature image, and a calculating unit configured to perform a convolution operation based on a pixel obtained by the first obtaining unit. The first obtaining unit is capable of obtaining non-adjacent pixels from the feature image.

Abstract: There is provided with a processing apparatus. A data holder holds at least some of data of a plurality of channels in a target layer among a plurality of layers. Each of a plurality of processors performs, in parallel, a product-sum operation using the data of one channel of the target layer and a coefficient corresponding to the target layer. A selector selects whether to perform first processing or second processing on the basis of information specifying processing in the target layer. The first processing includes inputting the data of one channel of the target layer into one of the plurality of processors. The second processing includes inputting the data of one channel of the target layer to the plurality of processors in parallel.

Abstract: A data processing apparatus comprises a holding unit configured to hold filter coefficients of a transferred filter, a generating unit configured to generate an extended filter by extending a size of the transferred filter while sequentially reading out the filter coefficients held in the holding unit, and an arithmetic unit configured to perform convolution by using filter coefficients of the extended filter.

Abstract: A data processing apparatus includes a storage unit configured to store reference data of a filter operation and coefficient data of filters, a plurality of operators configured to parallelly perform the filter operation on the reference data and the coefficient data of the filters, a first supply unit configured to supply reference data transferred from the storage unit to the plurality of operators, a second supply unit configured to supply coefficient data of a first and second filters transferred from the storage unit to the plurality of operators, and a control unit configured to control the second supply unit to supply the coefficient data of the first filter to a first operator, and supply the coefficient data of the second filter to a second operator.

Abstract: There is provided with a filter processing device for performing a convolution operation using a filter on a feature plane. An acquisition unit acquires feature plane data, filter coefficients of the filter, and valid coefficient information which specifies filter coefficients to be used in the convolution operation among the filter coefficients of the filter. A calculation unit performs a convolution operation of the filter coefficients specified by the valid coefficient information and pieces of the feature plane data corresponding to the specified filter coefficients.