Abstract: An image generation device includes an imaging unit configured to convert data representing an expression level for each microRNA type into image-rendition data serving as data representing a matrix of two dimensions or more, a classification unit configured to perform classification of the image-rendition data, and a contribution-presentation-image generation unit configured to generate a contribution-presentation image representing a contribution of a specific part of the image-rendition data to the classification.

Abstract: A neural network system includes a primary input layer configured to acquire data in both a learning mode and an operation mode, an auxiliary input layer configured to acquire data solely in the learning mode, a first partial network configured to carry out learning using both an output of the primary input layer and an output of the auxiliary input layer and to subsequently carry out learning solely using the output of the primary input layer so as to produce a same calculation result as a calculation result produced using both the output of the primary input layer and the output of the auxiliary input layer, and a second partial network configured to carry out calculations in the learning mode and the operation mode upon receiving an output of the first partial network.

Abstract: A neural network system includes a primary input layer configured to acquire data in both a learning mode and an operation mode, an auxiliary input layer configured to acquire data solely in the learning mode among the learning mode and the operation mode, a first partial network configured to carry out learning using both an output of the primary input layer and an output of the auxiliary input layer and to subsequently carry out learning solely using the output of the primary input layer among the primary input layer and the auxiliary input layer so as to produce a same calculation result as a calculation result produced using both the output of the primary input layer and the output of the auxiliary input layer, and a second partial network configured to carry out calculations in the learning mode and the operation mode upon receiving an output of the first partial network.

Abstract: The present invention relates to a categorical color perception system which automatically judges a categorical color and aims to judge a categorical color name correctly under various ambient lights. Test color measured at an experiment is inputted to an input layer portion corresponding to test color components 101, illumination light components at the experiment are inputted to an input layer portion corresponding to illumination light components 102, and connection weights are obtained by learning with backpropagation method so as to output a categorical color judged by an examinee.

Abstract: An image processor (1) for subjecting an image picked up by an imaging apparatus (21) to image processing to extract a specific object from the image, the image processor comprising: an image processing section (3) which subjects a plurality kinds of images (t, t?1, . . . , t?k) picked up by the imaging apparatus to the image processing based on a processing program comprising image filters (F) combined in a form of a tree structure, and which forms an output image (O) in which the specific object is extracted.