Panasonic Intellectual Property Corporation of America

Panasonic Intellectual Property Management Co., Ltd.

Panasonic Corporation

Dolby International Ab

Panasonic Intellectual Corporation of America

Yasunori Ishii

Tadamasa Toma

Yusuke Monobe

Masao Hiramoto

Sotaro Tsukizawa

Ryota Fujimura

Reiko Hagawa

Masaki Takahashi

Yohei Nakata

Hiroaki Urabe

Satoshi Sato

Tetsuji Fuchikami

Takuya Yamaguchi

Kazuki Kozuka

Katsuyoshi Yamagami

Yasunobu Ogura

Kazuyuki Imagawa

Toshihisa Nakano

Pongsak Lasang

Yasushi Yagi

Takashi Ushio

Tsutomu Muraji

Yasuhiro Mukaigawa

Eiji Fukumiya

Stefano Alletto

Kazutaka Furuta

Katsuhiro Iwasa

Changxin Zhou

Kunio Nobori

Teruyuki Takizawa

Luca Rigazio

Takahiro Yoneda

Masayuki Misaki

Masahiko Saito

Yukie Shoda

Yuta Shimotsuma

Toshiya Arai

Yuka Ozawa

Khang Nguyen

Mayu Yokoya

Denis A Gudovskiy

Takrit Tanasnitikul

Tsubasa Hirakawa

Takayoshi Yamashita

Hironobu Fujiyoshi

Tomoyuki Okuno

An information processing method performed by a computer includes: obtaining prediction results that are results of prediction performed by predictors on same input data; obtaining, for each of the prediction results, an influence that the input data had on the prediction result; determining, based on the prediction results, one or more combinations of the prediction results; and presenting, side by side or by superposition, using a presentation device, influences obtained for prediction results that are included in the prediction results and are in a same combination among the one or more combinations.

Information processing method for presenting influences obtained for prediction results, information processing system, and recording medium

An information processing apparatus includes: an obtainer that obtains sensing data; a common neutral network (NN) that inputs the sensing data into an inference model to obtain a result of inference and information on a processing time for a plurality of tasks subsequent to the processing performed by the inference model; and an NN inference computation management unit that determines a task schedule for a task processing unit that processes the plurality of subsequent tasks to process the plurality of subsequent tasks on the basis of the information on the processing time for the plurality of subsequent tasks and inputs the result of the inference into the task processing unit to process the plurality of subsequent tasks according to the determined task schedule.

Information processing apparatus, information processing method, and recording medium for performing inference processing using an inference model

A control device includes a parameter acquisition unit that acquires an augmentation parameter regarding geometric augmentation or optical augmentation of training data to be used for training a machine learning model, a display controller that causes a display device to display an image based on the augmentation parameter, an imaging controller that causes an imaging device to capture the displayed image, and an output unit that outputs the captured image obtained by the imaging device as the training data.

Control system and control method

Provided is a learning device that acquires computational imaging information of a computational imaging camera that captures an image with blurring; acquires a normal image captured by a normal camera that captures an image without blurring or an image with blurring smaller than that of the computational imaging camera, and a correct answer label assigned to the normal image; generates an image with blurring based on the computational imaging information and the normal image; and performs machine learning using the image with blurring and the correct answer label to create an image identification model for identifying an image captured by the computational imaging camera.

Learning method, image identification method, learning device, and image identification system

An image processing device includes a noise adder that obtains a captured image from an image capturing device including a mask having at least one aperture, an MPH information obtainer that obtains aperture pattern information corresponding to the pattern of the at least one aperture, the noise adder that adds, to the captured image, noise determined according to the aperture pattern information, and a transmitter that outputs the noise added captured image.

Image processing device, method for training machine learning model, identification device, and image processing method

An interval between a pinhole and a pinhole is set to a first interval at which a degree of superimposition of subject images captured through the corresponding pinholes falls within a predetermined range when an image of a subject located at a distance less than a predetermined distance from the multi-pinhole camera is captured. An interval between the pinhole and a pinhole is set to a second interval narrower than the first interval at which a degree of superimposition of subject images captured through the corresponding pinholes falls within a predetermined range when an image of the subject located at a distance equal to or more than the predetermined distance from the multi-pinhole camera is captured.

Multi-pinhole camera and image identification system

An information processing method includes: obtaining sensing data; determining a synthesis region in the sensing data in which recognition target data is to be synthesized with the sensing data; generating composite data by synthesizing the recognition target data into the synthesis region, the recognition target data having same or similar characteristics perceived by a human sensory system as the sensing data; obtaining recognition result data by providing the composite data to a model which has been trained using machine learning to recognize a recognition target; making a second determination based on the recognition result data and reference data including at least the synthesis region, the second determination being to determine whether to make a first determination, the first determination being to determine training data for the model based on the composite data; and making the first determination when it is determined in the second determination to make the first determination.

Information processing method and information processing system

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.

Information processing method of predicting calculation amount suitable for recognizing motion of object

A risk prediction method is executed by a computer of a risk predictor using a convolutional neural network. The method includes making the convolutional neural network acquire an input image taken by an in-vehicle camera installed on a vehicle. The method also includes making the convolutional neural network estimate a risk area and a feature of the risk area, the risk area being in the acquired input image. The risk area has a possibility that a moving object may appear from the risk area into a travelling path of the vehicle, and the moving object may collide with the vehicle in a case where the vehicle simply continues running. The method further includes making the convolutional neural network output the estimated risk area and the estimated feature of the risk area as a risk predicted for the input image.

Risk prediction method

An information processing method includes acquiring first output data for input data of first learning model, reference data for the input data, and second output data for the input data of second learning model obtained by converting first learning model; calculating first difference data corresponding to a difference between the first difference data and the reference data and second difference data corresponding to a difference between the second output data and the reference data; and training first learning model with use of the first difference data and the second difference data.

Information processing method and information processing system for reducing a difference between output data of a first learning model and output data of a second learning model

In a data processing method executed by a computer: inputting, in a third trained model, first output data corresponding to first input data for a first trained model to obtain second output data, the third trained model being acquired through training in which (i) output data of the first trained model is used as training data, and (ii) output data of a second trained model acquired by converting the first trained model is used as label data; obtaining first label data of the first input data; and retraining the first trained model using first differential data corresponding to differences between the second output data and the first label data.

Data processing method and data processing system

An information processing device is an information processing device including a processor. The processor obtains a detection result of a first detector for detecting a first target in first sensing data; and based on the detection result of the first detector, determines a setting of processing by a second detector for detecting a second target in second sensing data next in an order after the first sensing data, the second target being different from the first target.

Detection device, detection method, and recording medium for detecting an object in an image

An information processing method performed by a computer includes: obtaining a plurality of recognition result candidates in sensing data and a likelihood of each of the plurality of recognition result candidates, the plurality of recognition result candidates and the likelihood being obtained by inputting the sensing data to a model that is trained by machine learning and performs recognition processing; obtaining an indication designating a part to be analyzed in the sensing data; selecting at least one recognition result candidate from the plurality of recognition result candidates, based on (i) a relationship between each of the plurality of recognition result candidates and the part and (ii) the likelihood of each of the plurality of recognition result, candidates; and outputting the at least one recognition result candidate that is selected.

An information processing method is executed by a computer, and includes: obtaining a first image generated by a multi-pinhole camera; extracting at least one point spread function (PSF) in each of a plurality of regions in the first image; obtaining a second image different from the first image, and reference data used in machine learning for the second image; generating a third image, by convolving each of a plurality of regions in the second image with at least one PSF extracted in a corresponding region of the plurality of regions in the first image; and outputting a pair of the reference data and the third image.

Information processing method, information processing system, and information processing apparatus

An information processing device includes a processor. This processor: obtains at least one of first sensor data output from a first sensor and used to determine an ambient environment of a device in which a third sensor is placed, and second sensor data used to determine an orientation of this device; determines a tilt of a plane in a sensing direction of the third sensor with respect to the orientation of the device based on the at least one of the first sensor data and the second sensor data; determines, in accordance with the tilt determined, a processing target area of third sensor data output from the third sensor and used for object detection processing in the sensing direction of the third sensor; and executes the object detection processing using the processing target area determined, of the third sensor data.

Information processing device, information processing method, and recording medium

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Osaka, Japan

Yasunori Ishii