Boe Technology Group Co., Ltd.

Thomson Licensing

Boe Technology Groupco., Ltd.

Zhenglong Li

Lijie Zhang

Yingying Li

Pablo Navarrete Michelini

Xuewen Lv

Jianmin He

Lvwei Wang

Hui Li

Wenchu Dong

Xiaojun Ma

Jingyu Zhang

Mengmeng Sun

Liting Wu

The embodiments of the present disclosure disclose an image processing method and device. The image processing method comprises transforming a first image to obtain a plurality of second images; obtaining feature maps of each of the second images by performing feature extraction on the second images using a first machine learning unit selected from a group including at least one first machine learning unit; and inputting the feature maps of each of the second images to a second machine learning unit to obtain a processing result of the first image.

Image processing method and image processing device

A medical data cluster processing system, including: a cluster initiator device and cluster participant devices that have signal connection with each other. The cluster initiator device sends model data and medical data to at least two cluster participant devices; the cluster participant devices receive the model data and the medical data from the cluster initiator device, process the medical data based on the model data to obtain second processing data, and sends the second processing data to the cluster initiator device; and the cluster initiator device receives the second processing data sent from the at least two cluster participant devices, and comprehensively processes the second processing data to obtain a medical data processing result. A medical data processing method and a medical data cluster processing method are also provided.

Medical data processing method, cluster processing system and method thereof

The present disclosure provides a data processing method, a data processing device, and a computer readable storage medium. The data processing method includes: determining an encryption key according to first data; encrypting second data with the encryption key; and storing the first data in association with the encrypted second data.

Data processing method, data processing device, and computer readable storage medium

The present disclosure provides a liquid constant temperature heating apparatus, an infusion device and a formula milk preparation device. The liquid constant temperature heating apparatus includes: a heating portion, the heating portion having a heating chamber, and the heating chamber having a liquid inlet and a liquid outlet; a liquid inlet pipe, the liquid inlet pipe being connected with the liquid inlet of the heating portion; a liquid outlet pipe, the liquid outlet pipe being connected with the liquid outlet of the heating portion; a temperature sensor, the temperature sensor being arranged on the liquid outlet pipe and in communication with the heating portion; and a controller, which is in signal connection with the temperature sensor by a signal and configured to control heating of the heating portion according to a measurement result of the temperature sensor.

Liquid constant temperature heating apparatus, infusion device and formula milk preparation device

The present disclosure relates to an image processing method and a device, wherein the image processing method includes: acquiring a first image, the first image including an image formed with respect to a skin part of a patient to be diagnosed which needs diagnosis; inputting the first image into a neural network, to acquire position information of a pathologic change area in the first image; acquiring a boundary of the pathologic change area in the first image, acquiring an original image and a mask image which include the pathologic change area from the first image; fusing the mask image and the original image, obtaining a target image corresponding to the pathologic change area; wherein the target image is an image for diagnosing the pathologic change area, pixel points in the target image correspond to those in the original image and the mask image one by one.

Image processing method and device

The present disclosure provides a detection system and a detection method for intravenous injection leakage. The detection system for intravenous injection leakage, includes a detection module, configured to detect a status parameter of a skin at an acupuncture point; and an analysis module, configured to acquire the status parameter, and to determine whether the intravenous injection leakage happens or not depending on the status parameter.

Detection system and detection method for intravenous injection leakage

The present disclosure provides a method and an apparatus for detecting a 3D image, an electronic device, and a computer-readable medium. The method for detecting a 3D image includes layering a 3D image to obtain at least one 3D subimage. The 3D subimage contains a plurality of 2D images. The method includes performing an intra-layer clustering on the 3D subimage to obtain a superpixel grid. The method includes inputting the superpixel grid into a neural network for detecting. The method includes detecting, in response to detecting an object in the superpixel grid, the 3D subimage forming the superpixel grid containing the object to obtain and output a detection result.

3D image detection method and apparatus, electronic device, and computer readable medium

The present disclosure discloses a method and device for image encoding and a method and device for image decoding. The encoding method comprises steps of: downscaling an input high resolution HR image into a low resolution LR image by a downscaler; compressing the LR image using a first compression method; extracting an index value from at least one of the HR image and the LR image; determining a parameter from a parameter database using the index value; compressing the parameter using a second compression method different from the first compression method; and obtaining a data stream by merging the compressed parameter and the compressed LR image.

Method and device for image encoding and image decoding

A method and an electronic device for positioning an eyeball in a retinopathy image are disclosed. The method includes: using retinopathy image data with corresponding labeled data to train a deep learning network based on a loss function, so as to obtain a trained deep learning network; and processing retinopathy image data to be tested by using the trained deep learning network to obtain corresponding eyeball center coordinates and/or an eyeball diameter.

Method and electronic device for positioning eyeball in retinopathy image

A resolving method and a system, the method includes: creating a sample library by utilization of an original high-resolution (HR) image set; training a convolutional structural network by utilization of the sample library; and obtaining an HR output signal by processing a low-resolution (LR) input signal by utilization of the trained convolutional structural network. In the resolving method and system according to this disclosure, data after expansion may be processed by simple expansion hardware, without a large change algorithm; and complex algorithms are allocated into parallelizing design, and different servers operate mutually independent; and also, due to the modular design, the design proposals of functional modules may be modified by latter optimization.

Resolving method and system based on deep learning

The present application discloses a facial image processing apparatus. The facial image processing apparatus includes a memory; and one or more processor. The memory and the at least one processor are communicatively connected with each other. The memory stores computer-executable instructions for controlling the one or more processors to automatically identify a facial feature from a facial image; automatically extract an image portion defining the facial feature from the facial image; perform a detail enhancement process on the image portion to obtain a detail-enhanced image portion corresponding to the image portion; and perform an image composition process to compose the detail-enhanced image portion and the facial image to obtain an enhanced facial image.

Facial image processing apparatus, facial image processing method, and non-transitory computer-readable storage medium

According to the embodiments of the present disclosure, there is provided a method for detecting feature points in an image. The method comprises: processing data of the image using a first type of convolutional layers in a Convolutional Neural Network (CNN) to generate first processed data, wherein the first type of convolutional layers comprise convolution kernels having non-shared weights; processing the first processed data using a second type of convolutional layers in the CNN to generate second processed data, wherein the second type of convolutional layers comprise convolution kernels having shared weights; and determining the feature points in the image based on the second processed data. In addition, the embodiments of the present disclosure further provide a corresponding device and a corresponding computer readable storage medium.

Method, device, and computer readable storage medium for detecting feature points in an image

According to embodiments of the present disclosure, a method for processing an adaptive media service at an encoder includes a first acquisition step of acquiring a first data stream including first image encoding data obtained by encoding a first image sequence, a second acquisition step of acquiring at least one second data stream, each second data steam including second image encoding data obtained by encoding a second image sequence and a target optimization parameter corresponding to the second image encoding data, a first selection step of selecting one data stream from a first data stream set in accordance with a condition of the receiver, the first data stream set at least including the first data stream and the at least one second data stream, and a first transmission step of transmitting the selected data stream to the receiver.

Growing community of inventors

Beijing, China

Zhenglong Li