Abstract: A learning model generates a plurality of prototype vectors and generates an integrated similarity vector that indicates similarity between an input image and each prototype for a plurality of prototypes in accordance with similarity between one prototype vector and each pixel vector in a feature map acquired from an CNN. An image processing apparatus obtains prototype belongingness (distributed prototype belongingness) for each image by distributing prototype belongingness of a belonged prototype of each class to each of two or more images that belong to one class. Then, the learning model is subjected to machine learning in accordance with the distributed prototype belongingness of each prototype vector for each image so that each prototype vector is brought closer to any pixel vector in the feature map corresponding to each image.

Abstract: A training method includes: generating a first image by adding noise to a first area; generating a second image by adding noise to a second area; generating a combined image by weighted addition of the first image and the second image; generating a first training label for the first image; generating a second training label for the second image; generating a combined training label by weighted addition of the first training label and the second training label; and generating a learning model by machine learning using the combined image and the combined training label.

Abstract: An information processing method includes processing of: acquiring, from a plurality of time-series images in which an object is captured, first information including at least a plurality of positions or a plurality of sizes of the object; executing prediction processing of predicting second information including at least one of a position or a size of the object at a next time point in a time-series based on the first information and recursively executing the prediction processing based on the first information and the second information to predict the second information of the object at a time point further next to the next time point; executing recognition processing of recognizing motion of the object based on the second information; and determining a total number of times of recursion of the prediction processing based on a result of the recognition processing.

Abstract: A hydrogen production apparatus includes a heating furnace that burns fuel supplied by a fuel supply unit and heats catalyst particles, a cyclone that is connected to a downstream side of the heating furnace and separates the catalyst particles and a combustion exhaust gas, and a thermal decomposition furnace including a storage tank that stores the catalyst particles separated by the cyclone and a raw material gas introduction unit that introduces a raw material gas containing at least hydrocarbon from a lower portion of the storage tank.

Abstract: Each of tanks of a heat exchanger includes a tube joint portion and a tank body portion which define an internal space of the tank. The tube joint portions of the tanks constitute a single core plate. The tank body portions each have a claw protruding toward a core portion. The core plate is provided with a hole that fits with the claw. In a state in which the claw is fitted into the hole, the tank body portions are fixed to the core plate.

Abstract: Provided is a processor for a neural network whose high-performance compact model can be incorporated into low-spec devices such as embedded devices or mobile devices without requiring re-training. The processor for a neural network, which uses a multi-valued basis matrix, widens the range of integer values that can be taken by each element of the multi-valued basis matrix; thus, the number of dimensions (the number of elements) of a scaling coefficient vector is reduced accordingly. The elements of the scaling coefficient vector are real numbers, and thus reducing the amount of processing of real number calculation processing allows for reducing the number of dimensions (the number of elements) of the scaling coefficient vector. As a result, this neural network processor significantly reduces the amount of calculation processing while ensuring the calculation accuracy when performing matrix calculation processing using the binary basis matrix.

Abstract: An information processing method includes processing of: acquiring, from a plurality of time-series images in which an object is captured, first information including at least a plurality of positions or a plurality of sizes of the object; executing prediction processing of predicting second information including at least one of a position or a size of the object at a next time point in a time-series based on the first information and recursively executing the prediction processing based on the first information and the second information to predict the second information of the object at a time point further next to the next time point; executing recognition processing of recognizing motion of the object based on the second information; and determining a total number of times of recursion of the prediction processing based on a result of the recognition processing.

Abstract: Each of tanks of a heat exchanger includes a tube joint portion and a tank body portion which define an internal space of the tank. The tube joint portions of the tanks constitute a single core plate. The tank body portions each have a claw protruding toward a core portion. The core plate is provided with a hole that fits with the claw. In a state in which the claw is fitted into the hole, the tank body portions are fixed to the core plate.

Abstract: An object detecting device includes an image acquiring unit which acquires an image from a camera, a scanning interval calculating unit which calculates a scanning interval when a scanning window is scanned on the image based on a size on the image of a detection object that is detected by the detecting window, a scanning unit which scans on the image using the scanning interval that is calculated by the scanning interval calculating unit, and a detecting unit which determines whether the detection object is present within the scanned detecting window.

Abstract: A depth histogram is created for each of a plurality of local regions of the depth image by grouping, according to specified depths, the depth information for the individual pixels that are contained in the local regions. A degree of similarity between two of the depth histograms for two of the local regions at different positions in the depth image is calculated as a feature. A depth image for training that has a high degree of certainty is defined as a positive example, a depth image for training that has a low degree of certainty is defined as a negative example, a classifier that is suitable for classifying the positive example and the negative example is constructed, and an object that is a target of detection is detected in the depth image, using the classifier and based on the feature.

Abstract: An object detecting device includes an image acquiring unit which acquires an image from a camera, a scanning interval calculating unit which calculates a scanning interval when a scanning window is scanned on the image based on a size on the image of a detection object that is detected by the detecting window, a scanning unit which scans on the image using the scanning interval that is calculated by the scanning interval calculating unit, and a detecting unit which determines whether the detection object is present within the scanned detecting window.

Abstract: A fluidized bed gasification system is provided in which bed material and raw material are passed throughout a fluidized bed gasification furnace so that raw material is gasified with higher gasification efficiency to improve gasification productivity. A heat-resistant partition 32 for regulation of bed material flow is arranged between positions I and II of a downcomer 12 of a separator 8 and of a supply flow passage 25 in plane of a fluidized bed gasification furnace 2. As a result, the bed material introduced via the downcomer 12 is directed to a supply flow passage 25 through a circuitous flow passage 33 throughout the fluidized bed gasification furnace 2 defined by the heat-resistant partition 32.

Abstract: A depth histogram is created for each of a plurality of local regions of the depth image by grouping, according to specified depths, the depth information for the individual pixels that are contained in the local regions. A degree of similarity between two of the depth histograms for two of the local regions at different positions in the depth image is calculated as a feature. A depth image for training that has a high degree of certainty is defined as a positive example, a depth image for training that has a low degree of certainty is defined as a negative example, a classifier that is suitable for classifying the positive example and the negative example is constructed, and an object that is a target of detection is detected in the depth image, using the classifier and based on the feature.

Abstract: Provided are a method and a device for determining a shape match in three dimensions, which can utilize information relating to three-dimensional shapes effectively. Camera control means (33) of a determination device (10) captures a range image of an object as a determination target by using a range imaging camera (20). Feature point extraction means (34) extracts feature points based on the range image. Feature amount determination means (35) calculates a three-dimensional shape around the feature point as depths of surface points and determines a feature amount of the feature point based on the depths of the surface points. Match determination means (36) determines the match therebetween based on the feature amounts of the two shapes.

Abstract: An object recognition apparatus sets each of keypoints extracted from a typical image and one of keypoints extracted from an input image, having scale invariant features similar to each other, as a typical corresponding point and an object corresponding point matching with each other, and produces a position vector directed from a typical reference point of the typical image to each typical keypoint. The apparatus determines a position of an object reference point in the input image from a position of each object corresponding point and the vector of the typical corresponding point matching with the object corresponding point. When the positions of the object reference point are concentrated, the apparatus judges that an object picture having the object corresponding points in the input image matches with the typical image, and the apparatus recognizes the picture as an object indicated by the typical image.

Abstract: In a heat exchanger with a plurality of tubes, a header tank includes a core plate bonded to the tubes, a tank body fixed to the core plate, and an elastic member arranged between a bottom portion of a groove portion provided at an outer peripheral portion of the core plate and a tip end portion of the tank body to be elastically deformable therebetween. The elastic member is provided with a position determination portion which protrudes approximately in parallel with an inner bottom surface of the bottom portion of the groove portion. Furthermore, the position determination portion is configured in the elastic member to have a clearance between the position determination portion and the bottom surface of the bottom portion of the groove portion, and a clearance between the position determination portion and the tip end portion of the tank body.

Abstract: A fluidized bed gasification system is provided in which bed material and raw material are passed throughout a fluidized bed gasification furnace so that raw material is gasified with higher gasification efficiency to improve gasification productivity. A heat-resistant partition 32 for regulation of bed material flow is arranged between positions I and II of a downcomer 12 of a separator 8 and of a supply flow passage 25 in plane of a fluidized bed gasification furnace 2. As a result, the bed material introduced via the downcomer 12 is directed to a supply flow passage 25 through a circuitous flow passage 33 throughout the fluidized bed gasification furnace 2 defined by the heat-resistant partition 32.

Abstract: A method for detecting an ellipsoid includes: extracting an ellipsoid candidate; extracting an ellipsoid contour; calculating an ellipsoid parameter; calculating an adaptability ratio; and eliminating the ellipsoid candidate. Extracting the ellipsoid candidate includes: inputting an image with figures; selecting the ellipsoid candidate from the figures; and extracting a contour candidate point and a center point. Extracting the ellipsoid contour includes: drawing straight lines; determining contour candidate points; calculating first and second distances; and defining ellipsoid contour points. Calculating the ellipsoid parameter is based on the ellipsoid contour points and the center point. Calculating the adaptability ratio includes: drawing a complete ellipsoid; and calculating the adaptability ratio between the complete ellipsoid and the ellipsoid candidate. Eliminating the ellipsoid candidate is performed when the adaptability ratio is equal to or smaller than a threshold.

Abstract: A heat exchanger core includes a first tube, a second tube, a first fin, a second fin, and a connection member. The second tube is provided upstream of the first tube in a direction of air flow. The first fin is coupled to an outer surface of the first tube for facilitating heat exchange of the first tube. The second fin is coupled to an outer surface of the second tube for facilitating heat exchange of the second tube. The second fin is located upstream of the first fin to define a clearance therebetween. The connection member connects peaks of the first and second fins or connects valleys of the first and second fins.

Abstract: An object recognition apparatus sets each of keypoints extracted from a typical image and one of keypoints extracted from an input image, having scale invariant features similar to each other, as a typical corresponding point and an object corresponding point matching with each other, and produces a position vector directed from a typical reference point of the typical image to each typical keypoint. The apparatus determines a position of an object reference point in the input image from a position of each object corresponding point and the vector of the typical corresponding point matching with the object corresponding point. When the positions of the object reference point are concentrated, the apparatus judges that an object picture having the object corresponding points in the input image matches with the typical image, and the apparatus recognizes the picture as an object indicated by the typical image.