Abstract: A steering control device is provided with at least one of a first torque correction computing part and a second torque correction computing part; wherein the first torque correction computing part is equipped with a weight computing part which computes an increment of weight based on a magnitude of the driver torque, and accumulates the increment of weight to generate a weight, a clip value computing part which computes an automatic driver torque clip value according to the weight, and a clip processing part which clip processes the automatic driver torque with the automatic driver torque clip value; and the second torque correction computing part is equipped with a gain computing part which computes an increment of gain according to the driver torque, and accumulates the increment of gain to generate a gain, and a gain processing part which outputs an automatic driver torque multiplied by the gain.

Abstract: A server device includes: a reception unit configured to receive a RAW image from a terminal; and an image pipeline processing unit configured to develop the RAW image, wherein the image pipeline processing unit has: a first image processing unit configured to performing one or more image processes including at least pixel value adjustment on the RAW image and outputting an image-processed RAW image; and a second image processing unit configured to perform one or more image processes including at least demosaic on the RAW image image-processed by the first image processing unit and outputting a developed image.

Abstract: The image generation apparatus includes: an acquisition unit configured to acquire a base image, a reference image, the respective exposure values associated with the base image and the reference image, and a pseudo-exposure value different from the respective exposure values associated with the base image and the reference image; an estimation unit configured to estimate a conversion parameter; and a generation unit configured to generate a pseudo-image regarded as an image photographed with the pseudo-exposure value by converting the luminance value of the base image for each of the pixels based on the respective exposure values associated with the base image and the reference image, the pseudo-exposure value, and the conversion parameter.

Abstract: A training system comprises a training device, and a training data creation device for the training device. The training device trains a neural network by means of a backpropagation algorithm. The training data creation device acquires any one of a positive evaluation indicating that content of the input data coincides with the label, a negative evaluation indicating that content of the input data does not coincide with the label, and an ignorable evaluation indicating exclusion from a training target label, for each label regarding the input data to create training data.

Abstract: A device includes an acquiring unit acquiring a plurality of images including a first image, a second image, and a third image; a region detecting unit comparing pixel values of the first image and the third image to detect a moving object region; and a compositing unit generating a composite image by synthesizing a target image selected from a plurality of images and the second image wherein the compositing unit performs a ghost removing process for pixels of the target image corresponding to the moving object region and pixels of the second image corresponding to the moving object region to bring the pixel values of one of these images closer to the pixel values of the other image, and synthesizes the target image and the second image after the ghost removing process.

Abstract: A device includes an acquiring unit acquiring a plurality of images including a first image, a second image, and a third image; a region detecting unit comparing pixel values of the first image and the third image to detect a moving object region; and a compositing unit generating a composite image by synthesizing a target image selected from a plurality of images and the second image wherein the compositing unit performs a ghost removing process for pixels of the target image corresponding to the moving object region and pixels of the second image corresponding to the moving object region to bring the pixel values of one of these images closer to the pixel values of the other image, and synthesizes the target image and the second image after the ghost removing process.

Abstract: A training system comprises a training device, and a training data creation device. The training device trains a neural network. The training data creation device acquires any one of a positive evaluation indicating that content of the input data coincides with the label, a negative evaluation indicating that content of the input data does not coincide with the label, and an ignorable evaluation indicating exclusion from a training target label, for each label regarding the input data to create training data. In training the neural network for training, the training system adjusts the weight coefficient for the intermediate layer and makes the recognition score of the label with the ignorable evaluation not affect the adjustment of the weight coefficient for the intermediate layer.

Abstract: An image processing apparatus includes: an alignment unit configured to perform alignment for a group of images including a plurality of short-time-exposure images that are captured with a first exposure time and a long-time-exposure image that is captured with a second exposure time that is longer than the first exposure time; and an output unit configured to output the long-time-exposure image in a case where the long-time-exposure image satisfies a predetermined condition and configured to output a composite image which is generated by compositing a plurality of images selected from among the plurality of short-time-exposure images, in a case where the long-time-exposure image does not satisfy the predetermined condition.

Abstract: An image processing apparatus includes: an alignment unit configured to perform alignment for a group of images including a plurality of short-time-exposure images that are captured with a first exposure time and a long-time-exposure image that is captured with a second exposure time that is longer than the first exposure time; and an output unit configured to output the long-time-exposure image in a case where the long-time-exposure image satisfies a predetermined condition and configured to output a composite image which is generated by compositing a plurality of images selected from among the plurality of short-time-exposure images, in a case where the long-time-exposure image does not satisfy the predetermined condition.

Abstract: The image generation apparatus includes: an acquisition unit configured to acquire a base image, a reference image, the respective exposure values associated with the base image and the reference image, and a pseudo-exposure value different from the respective exposure values associated with the base image and the reference image; an estimation unit configured to estimate a conversion parameter; and a generation unit configured to generate a pseudo-image regarded as an image photographed with the pseudo-exposure value by converting the luminance value of the base image for each of the pixels based on the respective exposure values associated with the base image and the reference image, the pseudo-exposure value, and the conversion parameter.

Abstract: A training system comprises a training device, and a training data creation device. The training device trains a neural network. The training data creation device acquires any one of a positive evaluation indicating that content of the input data coincides with the label, a negative evaluation indicating that content of the input data does not coincide with the label, and an ignorable evaluation indicating exclusion from a training target label, for each label regarding the input data to create training data. In training the neural network for training, the training system adjusts the weight coefficient for the intermediate layer and makes the recognition score of the label with the ignorable evaluation not affect the adjustment of the weight coefficient for the intermediate layer.

Abstract: The present disclosure is to generate a high-quality image by correcting a predetermined correction target image based on a plurality of input images. In an image processing device 3, an image correcting section 160 detects a user tap gesture on a touch panel 250. When the position of the tap gesture is within foreground candidate areas detected by a foreground candidate area detecting section 140, the image correcting section 160 corrects a base image set by a base image setting section 120 in the areas corresponding to the foreground candidate areas.

Abstract: An image composition device composites a no-flash image including a subject captured under ambient light and a flash image including the subject captured by emitting flash light to generate a composite image including the subject. The image composition device includes an input unit that enables the no-flash image and the flash image to be input, a correction unit that corrects the no-flash image and the flash image input from the input unit, and a composition unit that composites the no-flash image and the flash image output from the correction unit to generate a composite image. The correction unit corrects a color temperature of the no-flash image.

Abstract: The image processing device performs noise removal processing for an input image. The image processing device comprises a filter setting unit configured to set first and second filter factors by using a first target pixel value of a noise processing target pixel to be targeted to the processing and a reference pixel value of a plurality of reference pixels surrounding the noise processing target pixel and a noise removal unit configured to calculate a corrected pixel value by sequentially adding a luminance component of the reference pixel value weighted with the first filter factor and sequentially adding a chroma component of the reference pixel value weighted with the second filter factor, and remove noise of the noise processing target pixel by using the corrected pixel value. The input image has pixel values according to Bayer pattern format.

Abstract: There is provided an information processing apparatus, the information processing apparatus including: a control unit configured to cause a second information processing apparatus to output authentication key information for allowing a first information processing apparatus to make a wireless connection with the second information processing apparatus in order to conduct data transmission from the first information processing apparatus to the second information processing apparatus using wireless communication, and determine to allow the first information processing apparatus to make the wireless connection on the basis of authentication key information input into the first information processing apparatus and the output authentication key information.

Abstract: An information processing device includes circuitry configured to acquire service information for a service from a first information processing apparatus, change a priority of the service based on a status of the information processing apparatus or a status of the service, and provide the service information to a second information processing apparatus based on the priority.

Abstract: Methods and apparatus for operating a first apparatus in a communication system. The method comprises receiving content from a second apparatus, and determining whether to store the received content on at least one storage apparatus associated with the first apparatus based, at least in part, on priority information associated with the received content, the priority information indicating an evaluation of a service provided by the received content.

Abstract: An image synthesis apparatus for generating a composite image by synthesizing a second image with a first image, includes an image acquisition unit configured to acquire first group images including the first image and a plurality of different resolution images corresponding to the first image, and second group images including the second image and a plurality of different resolution images corresponding to the second image, a frequency component calculation unit configured to calculate low-frequency components and high-frequency components from the first group images and the second group images, and an image synthesis unit configured to generate the composite image on the basis of the low-frequency components of the first group images and the high-frequency components of the second group images.

Abstract: The present disclosure is to generate a high-quality image by correcting a predetermined correction target image based on a plurality of input images. In an image processing device 3, an image correcting section 160 detects a user tap gesture on a touch panel 250. When the position of the tap gesture is within foreground candidate areas detected by a foreground candidate area detecting section 140, the image correcting section 160 corrects a base image set by a base image setting section 120 in the areas corresponding to the foreground candidate areas.

Abstract: There is provided a communication apparatus including a communication unit having an optical communication scheme and a different communication scheme from the optical communication scheme, a level setting unit configured to set a security level in data communication, and a communication scheme switching unit configured to switch communication schemes of the communication unit in accordance with the security level that is set by the level setting unit.