Kabushiki Kaisha Toshiba

Sumitomo Electric Industries, Limited

Canon Medical Systems Corporation

Sumitomo Electric Device Innovations, Inc.

Kabushiki Kaisha

Toshimitsu Kaneko

Osamu Hori

Takeshi Mita

Koji Yamamoto

Takashi Ida

Nobuyuki Matsumoto

Hidenori Takeshima

Koichi Masukura

Yasunori Taguchi

Kenzo Isogawa

Toshiyuki Ono

Noboru Yamaguchi

Nao Mishima

Satoshi Kawata

Yoshihiro Ohmori

Kanako Saito

Toshiaki Watanabe

Yoshinori Suzuki

Tatsunori Kanai

Takeshi Saito

Hiroshi Yao

Toru Kambayashi

Kenichi Shimoyama

Takeshi Aikawa

Shigeru Oyanagi

Tooru Kamibayashi

Toshihiro Morohoshi

Shigeyasu Natsubori

Hisashi Aoki

Takahiro Harashima

Yoko Sambonsugi

Hideaki Sato

Shuhei Nitta

Tomoya Kodama

Tatsuya Tanaka

Toshinari Takahashi

Tatsuo Kozakaya

Ryosuke Nonaka

Susumu Kubota

Yasutoyo Takeyama

Yusuke Moriuchi

Yoshie Imai

Mai Murashima

Kazuhiko Taira

Hideki Mimura

Masahiro Baba

Satoshi Ito

Yasufumi Tsumagari

Shinsuke Tsukagoshi

Tomoyuki Takeguchi

Yasuhiro Ishibashi

Takuma Yamamoto

Tatsuya Kimoto

Wataru Watanabe

Tomohisa Imamura

Haruhiko Toyama

Tsutomu Ishikawa

Shunichi Numazaki

Tadaaki Masuda

Wataru Asano

Takuya Fujii

Naoki Endoh

Ryota Osumi

Seiichi Nakamura

Chie Fukuda

Phillip J Edwards

Noriyuki Hirayama

Rie Katsuki

Norihiro Nakamura

Taro Hasegawa

Tomoya Okazaki

Takero Kobayashi

Eita Shuto

Atsushi Yaguchi

Go Ito

Tomohiro Nakai

Junya Takakura

Masami Ishiura

Yoichiro Yamagata

Yukie Takahashi

Lance Thompson

Kei Imada

Toshiyuki Taguchi

Misaki Haratake

Marco Visentini Scarzanella

A route planning device includes a memory and one or more processors coupled to the memory. The one or more processors are configured to: calculate a tentative route passing through a plurality of tour points disposed in a virtual space that is acquired by removing an obstacle from a space including the obstacle; and derive a route with one or more via points added around an interference point between the obstacle included in the space and the tentative route with a calculation accuracy corresponding to a precision of via point calculation.

Route planning device, route planning method, and computer program product

An information processing device includes processing circuitry. The processing circuitry is configured to acquire one or more pieces of first state information representing a state of each of one or more second subjects related to a first subject to be a subject of inference at first time, and one or more pieces of second state information representing a state of each of the one or more second subjects at second time; and generate learning data for use in reinforcement learning of a machine learning model for use in inference. The learning data includes the first state information at least part of which is replaced with any of the one or more pieces of the second state information, and the second state information at least part of which is replaced with any of the one or more pieces of the first state information.

Information processing device, information processing method, and computer program product

A magnetic resonance imaging apparatus according to an embodiment includes an MRI system and a processing circuitry. The MRI system includes a receiving coil to receive a magnetic resonance signal. The processing circuitry is configured to generate an image based on the magnetic resonance signal, the image including a plurality of pixels; calculate a feature value corresponding to a signal value of the pixel; correct the feature values based on a sensitivity of the receiving coil; and reduce noise in the image based on distribution of the corrected feature values.

Magnetic resonance imaging apparatus, image processing apparatus, and image processing method

According to one embodiment, a learning method, comprises receiving a first signal including a previous auxiliary variable value, previous action information regarding a previous action, or a set of previous scores, receiving current sensor data, selecting a current action of the control target based on the first signal, the current sensor data, and a parameter for obtaining a score from sensor data, causing the control target to execute the current action, receiving next sensor data and a reward, and updating the parameter based on the current sensor data, current action information regarding the current action, the next sensor data, and the reward. A degree of selecting a previous action as the current action is increased.

Learning method and program

According to one embodiment, a robot motion planning device includes processing circuitry. The processing circuitry receives observation information obtained by observing at least part of a movable range of a robot. The processing circuitry determines, in a case where first observation information is received, a target position to which the robot is to make a motion, using an action-value function and the first observation information. The processing circuitry receives measurement information obtained by measuring a state of the robot, calculates a difference corresponding to the first observation information, using the measurement information, and determines a motion plan of a force-controlled motion of the robot, based on the target position and the difference.

Robot motion planning device, robotic system, and method

An image processing apparatus includes processing circuitry configured: to obtain a plurality of images taken so as to include a target site of a subject in temporal phases; and to calculate an index indicating a state of an adhesion at a boundary between a first site of the subject corresponding to a first region and a second site of the subject corresponding to a second region, by using classification information used for classifying each of pixels into one selected from between a first class related to the first region and a second class related to a second region positioned adjacent to the first region in a predetermined direction, on a basis of mobility information among the images in the temporal phases with respect to the pixels in the images that are arranged in the predetermined direction across the boundary between the first region and the second region of the images.

Image processing apparatus and medical image taking apparatus

An ultrasound diagnosis apparatus according to an embodiment includes processing circuitry. The processing circuitry obtains time-series data having complex values based on a reflected wave of an ultrasound wave transmitted by an ultrasound probe and calculates an expansion coefficient in a case in which the obtained time-series data is expressed as a linear sum of a plurality of mathematical functions, the time-series data having, as an argument, a first parameter related to time. The plurality of mathematical functions are mathematical functions that are possible to be generated on a basis of a function family that has, as arguments, the first parameter and a second parameter different from the first parameter.

Ultrasound diagnosis apparatus, signal processing apparatus, and signal processing method

According to an embodiment, a network training device includes a first training unit that trains a first network that converts an input signal to a first signal, a second training unit that trains a second network that converts the first signal to a second signal, and a third training unit that trains a third network that converts the second signal to an output signal. The first training unit trains the first network as an encoder of a first autoencoder. The second training unit trains the second network by backpropagation by using a second signal for training corresponding to the first signal for training as supervised data. The second signal for training is generated by an encoder of a second autoencoder that encodes a third signal for training into the second signal for training, and decodes the second signal for training into the third signal for training.

Network training device, network training system, network training method, and computer program product

A process of forming a semiconductor optical device is disclosed. The semiconductor optical device provides a waveguide structure accompanied with a heater for varying a temperature of the waveguide structure. The process includes steps of: (a) forming a striped mask on a semiconductor substrate; (b) selectively growing a dummy layer on the semiconductor substrate; (c) removing the patterned mask; (d) burying the dummy layer by a supplemental layer; (e) exposing a portion of the dummy layer by etching a portion of the supplemental layer; (f) and removing the dummy layer by immersing the dummy layer within a solution that shows an etching rate for the dummy layer enough faster than an etching rate for the supplemental layer and the substrate so as to leave a void in a region the dummy layer had existed.

Process of forming epitaxial substrate and semiconductor optical device

An optical semiconductor device is provided as one achieving reduction of power in phase control. The optical semiconductor device has: a first optical waveguide having a plurality of segments each of which has a diffraction grating region with a diffraction grating and a space portion coupled to the diffraction grating region, having two ends interposed between the diffraction grating regions, and having a constant optical length, wherein at least one of the segments is provided with a phase shift structure; a first phase control device for adjusting a phase of light in each segment with the phase shift structure; and a second phase control device for adjusting a phase of light in each segment without the phase shift structure.

Optical semiconductor device

According to one embodiment, an electronic device includes circuitry. The circuitry is configured to: receive first image data for displaying a first image that comprises a plurality of regions, modify a first region of the first image by adding at least a high-frequency component based on second image data, the first region of the first image including fewer noise components than a first threshold, and output third image data for displaying the first image that comprises the plurality of regions and the modified first region.

Electronic device, method, and computer program product

According to one embodiment, a motion vector detection apparatus includes following units. The layering unit generates layers with different resolutions for each of first and second images. The first extraction unit extracts a space candidate vector. The second extraction unit extracts a time candidate vector. The third extraction unit extracts a layer candidate vector. The determination unit determines a motion vector to be assigned to the target block, based on correlations between the target block and blocks, the blocks being located in a layer which corresponds to the second image and being specified by assigning, to the target block, the space, time, and layer candidate vectors.

Motion vector detection apparatus and method

An image processing device includes processing circuitry configured to acquire a plurality of basis patterns for converting a first region and a second region in a target image, calculate a contribution ratio of each basis pattern, and select one or more basis patterns from higher contribution ratio to lower contribution ratio until a sum of contribution ratios of the selected one or more basis patterns reaches a specific first threshold. The processing circuitry is further configured to generate a control signal of an intensity that increases with a number of the one or more selected basis patterns, project a third region in the target image to the basis patterns to obtain a projection coefficient, reduce noise of the projection coefficient based on the intensity of the control signal, and reconstruct the third region using the projection coefficient after the noise is reduced.

Device and method of image processing for denoising based on degree of concentration of contribution ratios of basis patterns

According to an image processing apparatus includes an acquisition unit, a storage unit, and a convolution unit. The acquisition unit is configured to acquire an input image captured via an optical system. The storage unit is configured to store therein a coefficient designed through learning for each of positions of respective pixel sets referred to in a convolution such that a result of the convolution of a second image with the coefficient is brought nearer to a first image, the second image being obtained by deteriorating the first image through a predetermined deterioration process. The convolution unit is configured to read the coefficient from the storage unit correspondingly to a position of a pixel set referred to in the input image, and generate an output image by convoluting the pixel set with the coefficient.

Image processing apparatus, image processing method, and imaging apparatus

Growing community of inventors

Yokohama, Japan

Toshimitsu Kaneko