Abstract: A data analysis apparatus is provided with a graph data generation unit that generates, in chronological order, a plurality of items of graph data configured by combining a plurality of nodes representing attributes for each element and a plurality of edges representing relatedness between the plurality of nodes, a node feature vector extraction unit that extracts a node feature vector for each of the plurality of nodes, an edge feature vector extraction unit that extracts an edge feature vector for each of the plurality of edges, and a spatiotemporal feature vector calculation unit that calculates a spatiotemporal feature vector indicating a change in node feature vector by performing, on the plurality of items of graph data generated by the graph data generation unit, convolution processing for each of a space direction and a time direction on the basis of the node feature vector and the edge feature vector.

Abstract: Provided are: an amodal segmentation unit that generates a set of first amodal masks indicating a probability that a particular pixel belongs to a relevant object for each of objects, with respect to an input image in which a plurality of the objects partially overlap; an overlap segmentation unit that generates an overlap mask corresponding only to an overlap region where the plurality of objects overlap in the input image based on an aggregate mask obtained by combining the set of first amodal masks generated for each of the objects and a feature map generated based on the input image; and an amodal mask correction unit that generates and outputs a second amodal mask, which includes an annotation label indicating a category of each of the objects corresponding to a relevant pixel, for each of pixels in the input image using the overlap mask and the aggregate mask.

Abstract: The invention supports creation of models for recognizing attributes in an image with high accuracy. An image recognition support apparatus includes an image input unit configured to acquire an image, a pseudo label generation unit configured to recognize the acquired image based on a plurality of types of image recognition models and output recognition information, and generate pseudo labels indicating attributes of the acquired image based on the output recognition information, and a new label generation unit configured to generate new labels based on the generated pseudo labels.

Abstract: In a current image processing environment, providing feedback for a user operation is slow, and a user cannot confirm the result of the operation in real time. Thus, the user interrupts the operation every time the user confirms the feedback, and a time period for performing image processing is long. An image processing device includes a guidance information generator. The guidance information generator acquires trajectory information to be used to segment an image object on an image input from a user, generates guidance information indicating a segmentation region desired by the user based on the trajectory information, and presents the segmentation region based on a user's intention in real-time. The guidance information generator provides a function of smoothly continuously segmenting an image object.

Abstract: Flow barriers such as trenches (144) and/or walls (152) laterally surrounding an aperture (142) in a coating (140) on a transparent substrate (120) help control the flow of replication material (124) during the formation of a replicated optical element on the aperture (142).

Abstract: A video processing apparatus that processes a video of a moving body captured by a camera is configured to sample frames output from the camera at a predetermined rate, calculate a direction of motion of the moving body based on a sequence of a plurality of the frames, and extract a feature amount of the video by performing convolution processing together on the plurality of the frames based on the calculated direction.

Abstract: Provided are: an amodal segmentation unit that generates a set of first amodal masks indicating a probability that a particular pixel belongs to a relevant object for each of objects, with respect to an input image in which a plurality of the objects partially overlap; an overlap segmentation unit that generates an overlap mask corresponding only to an overlap region where the plurality of objects overlap in the input image based on an aggregate mask obtained by combining the set of first amodal masks generated for each of the objects and a feature map generated based on the input image; and an amodal mask correction unit that generates and outputs a second amodal mask, which includes an annotation label indicating a category of each of the objects corresponding to a relevant pixel, for each of pixels in the input image using the overlap mask and the aggregate mask.

Abstract: An image retrieving apparatus includes a pose estimating unit which recognizes pose information of a retrieval target including a plurality of feature points from an input image, a features extracting unit which extracts features from the pose information and the input image, an image database which accumulates the features in association with the input image, a query generating unit which generates a retrieval query from pose information specified by a user, and an image retrieving unit which retrieves images including similar poses according to the retrieval query from the image database.

Abstract: Provided is technique of object recognition that can accurately recognize an object. An object recognition apparatus (i) generates property data that highlights a specific property based on target data, (ii) extracts a discrimination-use feature amount used for discrimination of each piece of the property data, (iii) calculates discrimination information used for discrimination of the property data, (iv) extracts a reliability feature amount used for estimation of reliability of the discrimination information calculated for each piece of the property data, (v) estimates the reliability of the discrimination information, (vi) generates synthesized information acquired by synthesizing the discrimination information calculated for each piece of the property data and the reliability calculated for each piece of the property data, and (vii) performs processing related to the object recognition.

Abstract: The online recognition apparatus includes a feature amount extraction unit that extracts a feature amount of input data, an identification result prediction unit that predicts an identification result based on the extracted feature amount, a prediction result evaluation unit that determines necessity of labeling from the predicted identification result unit, a correct answer assigning unit that assigns a correct answer to input data online from the determination result, a generator update unit that updates a parameter of a generator based on the input data with the correct answer, a pseudo-learning data generation unit that establishes a generator based on the parameter of the updated generator and generates pseudo-learning data, and an identifier update unit that online updates a parameter of an identifier prepared in advance based on the input data with the correct answer and the pseudo-learning data. The updated identifier is updated as a new identification result prediction unit.

Abstract: In a current image processing environment, providing feedback for a user operation is slow, and a user cannot confirm the result of the operation in real time. Thus, the user interrupts the operation every time the user confirms the feedback, and a time period for performing image processing is long. An image processing device includes a guidance information generator. The guidance information generator acquires trajectory information to be used to segment an image object on an image input from a user, generates guidance information indicating a segmentation region desired by the user based on the trajectory information, and presents the segmentation region based on a user's intention in real-time. The guidance information generator provides a function of smoothly continuously segmenting an image object.

Abstract: Provided is technique of object recognition that can accurately recognize an object. An object recognition apparatus (i) generates property data that highlights a specific property based on target data, (ii) extracts a discrimination-use feature amount used for discrimination of each piece of the property data, (iii) calculates discrimination information used for discrimination of the property data, (iv) extractsa reliability feature amount used for estimation of reliability of the discrimination information calculated for each piece of the property data, (v) estimates the reliability of the discrimination information, (vi) generates synthesized information acquired by synthesizing the discrimination information calculated for each piece of the property data and the reliability calculated for each piece of the property data, and (vii) performs processing related to the object recognition.

Abstract: An image retrieving apparatus includes a pose estimating unit which recognizes pose information of a retrieval target including a plurality of feature points from an input image, a features extracting unit which extracts features from the pose information and the input image, an image database which accumulates the features in association with the input image, a query generating unit which generates a retrieval query from pose information specified by a user, and an image retrieving unit which retrieves images including similar poses according to the retrieval query from the image database.

Abstract: The present invention provides piperidin-4-yl azetidine derivatives, as well as their compositions and methods of use, that modulate the activity of Janus kinase 1 (JAK1) and are useful in the treatment of diseases related to the activity of JAK1 including, for example, inflammatory disorders, autoimmune disorders, cancer, and other diseases.