Abstract: A neural network is provided. The neural network includes 2n number of sampling units sequentially connected; and a plurality of processing units. A respective one of the plurality of processing units is between two adjacent sampling units of the 2n number of sampling units. A first sampling unit to an n-th sample unit of the 2n number of sampling units are DeMux units. A respective one of the DeMux units is configured to rearrange pixels in a respective input image to the respective one of the DeMux units following a first scrambling rule to obtain a respective rearranged image. An (n+1)-th sample unit to a (2n)-th sample unit of the 2n number of sampling units are Mux units. A respective one of the Mux units is configured to combing respective m? number of input images to the respective one of the Mux units to obtain a respective combined image.

Abstract: A neural network is provided. The neural network includes 2n number of sampling units sequentially connected; and a plurality of processing units. A respective one of the plurality of processing units is between two adjacent sampling units of the 2n number of sampling units. A first sampling unit to an n-th sample unit of the 2n number of sampling units are DeMux units. A respective one of the DeMux units is configured to rearrange pixels in a respective input image to the respective one of the DeMux units following a first scrambling rule to obtain a respective rearranged image. An (n+1)-th sample unit to a (2n)-th sample unit of the 2n number of sampling units are Mux units. A respective one of the Mux units is configured to combine respective m? number of input images to the respective one of the Mux units to obtain a respective combined image.

Abstract: An image processing method implemented by a computing device is described herein, which includes acquiring an image to be processed and a target style of image, the image to be processed being an image of a second resolution level, and inputting the image to be processed and the target style into a trained image processing neural network for image processing to obtain a target image of the target style, the target image being an image of a first resolution level. The resolution of the image of the first resolution level is higher than that of the image of the second resolution level.

Abstract: The present disclosure relates to an image processing method. The image processing method may include upscaling a feature image of an input image by an upscaling convolutional network to obtain a upscaled feature image; downscaling the upscaled feature image by a downscaling convolutional network to obtain a downscaled feature image; determining a residual image between the downscaled feature image and the feature image of the input image; upscaling the residual image between the downscaled feature image and the feature image of the input image to obtain an upscaled residual image; correcting the upscaled feature image using the upscaled residual image to obtain a corrected upscaled feature image; and generating a first super-resolution image based on the input image using the corrected upscaled feature image.

Abstract: The present disclosure discloses a convolutional neural network processor, an image processing method and an electronic device. The method includes: receiving, by the first convolutional unit, the input image to be processed, extracting the N feature maps with different scales in the image to be processed, sending the N feature maps to the second convolutional unit, and sending the first feature map to the processing unit; fusing, by the processing unit, the received preset noise information and the first feature map, to obtain the second feature map, and sending the second feature map to the second convolutional unit; and fusing, by the second convolutional unit, the received N feature maps with the second feature map to obtain the processed image.

Abstract: A contactless gesture control method, applied to a terminal equipped with a full-time working sensor, includes: detecting a contactless gesture by the full-time working sensor; acquiring an application operation instruction corresponding to the contactless gesture when the contactless gesture is detected by the full-time working sensor; and executing the application operation instruction.

Abstract: Provided are a data interaction method and device, a storage medium, and a mobile terminal. The data interaction method is used for a mobile terminal. The mobile terminal includes dual cameras.

Abstract: A computer-implemented method of training a convolutional neural network configured to morph content features of an input image with style features of a style image is provided. The computer-implemented method includes selecting a training style image; extracting style features of the training style image; selecting a training content image; extracting content features of the training content image; processing the training content image through the convolutional neural network to generate a training output image including the content features of the training content image morphed with the style features of the training style image; extracting content features and style features of the training output image; computing a total loss; and tuning the convolutional neural network based on the total loss including a content loss, a style loss, and a regularization loss.

Abstract: The present disclosure provides a training method for generative adversarial network, which includes: extracting a first-resolution sample image from a second-resolution sample image; separately providing a first input image and a second input image for a generative network to generate a first output image and a second output image respectively, the first input image including a first-resolution sample image and a first noise image, the second input image including the first-resolution sample image and a second noise image; separately providing the first output image and a second-resolution sample image for a discriminative network to output a first discrimination result and a second discrimination result; and adjusting parameters of the generative network to reduce a loss function. The present disclosure further provides an image processing method using the generative adversarial network, a computer device, and a computer-readable storage medium.

Abstract: An apparatus includes a signal modulator configured to receive a radio frequency (RF) input signal having frequency bands and spanning a first frequency range within a second frequency range, and provide down-converted signals by converting each frequency band of the RF input signal down to a target frequency range. The apparatus further includes digital RF memories (DRFMs) configured to provide intermediate interfering signals by modulating at least one of the down-converted signals, and an interfering signal generator configured to provide up-converted signals by converting the intermediate interfering signals collectively up to a third frequency range, wherein the third frequency range is within the second frequency range, and provide an interfering RF output signal by combining the up-converted signals, wherein the interfering RF output signal spans the third frequency range.

Abstract: Disclosed is a two-dimensional code image generation method and apparatus, a storage medium and an electronic device related to the field of two-dimensional code image technology. The method includes obtaining an initial two-dimensional code image and a background image, and performing structured processing on the initial two-dimensional code image according to the background image to obtain a structured two-dimensional code image, performing mode transfer processing on the background image to obtain a background image of a target mode by a mode transfer model, and performing a fusion operation on the structured two-dimensional code image and the background image of the target mode to obtain a target two-dimensional code image.

Abstract: An image processing method implemented by a computing device is described herein, which includes acquiring an image to be processed and a target style of image, the image to be processed being an image of a second resolution level, and inputting the image to be processed and the target style into a trained image processing neural network for image processing to obtain a target image of the target style, the target image being an image of a first resolution level. The resolution of the image of the first resolution level is higher than that of the image of the second resolution level.

Abstract: Systems and methods are provided for wireless charging. The system includes an intelligent management device and a wireless charging transmitter. The intelligent management device is configured to: receive a wireless charging request from the mobile terminal; generate a wireless charging instruction according to the first location information of the mobile terminal and the charging location information of the wireless charging transmitter; and send the wireless charging instruction to the wireless charging transmitter. The wireless charging transmitter is configured to: receive the wireless charging instruction; determine a transmitting direction according to the direction information in the wireless charging instruction; and transmit a wireless energy wave in the transmitting direction.

Abstract: Provided herein are methods for treating or preventing a cancer, including solid tumors and hematological cancers, comprising administering an effective amount of aminopurine compounds of formula (I), and compositions comprising an effective amount of such compounds.

Abstract: An image processing method, an image processing device and a computer storage medium are provided. The method includes: performing a maximum-filtering processing on an original image and obtaining a luminance channel of the image; and performing a guided-filtering processing on the obtained luminance channel, and estimating and obtaining an incident component.

Abstract: A display box is provided for housing and retaining a cylindrical container. The box may include two side walls and a front and rear wall, a top lid extending from an upper end of one of the walls and a bottom lid extending from the lower end of the same or a different wall. At least one elongate flap further extends from the lower end of one of said side walls or rear wall, said flap being provided with crease lines along which said flap may be folded. The flap has an end portion adhered to the inner surface of the wall from which the flap extends, a first lateral portion having a proximal end adjacent the wall and a distal end extending into the box. A vertical portion extends down from the distal end of the first lateral portion and a second lateral portion connects a lower end of the vertical portion and a distal end of a base portion.

Abstract: A power conversion system is disclosed, which comprises at least one conversion unit comprising a converter unit and a first power interface boards; at least one measurement unit comprising a measurement board and a second power interface boards; and a controller comprising a processing unit, and a third power interface board communicated with the processing unit, and the first power interface board and the second power interface board, wherein at least some of the communications between the third power interface board and the first and second power interface boards have independent bandwidths.

Abstract: A selection of a plurality of graphical user interface (GUI) components of a GUI is received. The selection is received so that the GUI can be tested. Attributes of the selection of GUI components are determined. Using the attributes, a default procedure for testing the GUI is determined. The default procedure includes a first set of input values for GUI components of the plurality of GUI components. The default procedure includes a first sequence in which the first set of input values are provided. Modifications to the default procedure are received. Using the modifications, a final procedure with a second set of input values provided in a sequence is generated. The GUI is tested with the final procedure. Testing the GUI includes providing the second set of input values to respective GUI components in the second sequence.

Abstract: Provided is an image formation system including an image formation device and a post-processing device configured to convey a paper sheet on which an image has been formed at the image formation device or carry out post-processing thereon, including: a paper ejection tray on which the discharged paper sheet is placed; a jam detector configured to detect a jam of the paper sheet conveyed in a paper conveyance passage; a partition paper sheet inserter configured to insert a partition paper sheet on the paper ejection tray; and a control unit, wherein the control unit controls the partition paper sheet inserter such that, after the jam is detected and paper sheets to be removed, at least including a responsible paper sheet, are removed, the partition paper sheet is inserted on the paper ejection tray before the paper sheet remaining in the paper conveyance passage is discharged to the paper ejection tray.

Abstract: The innovations provides an antimicrobial and synergistic phytochemical composition, consisting of two active ingredients (FZ and YC). This innovation also consists of formulation processes and its applications to fungi, bacteria and/or virus-caused plant diseases such as citrus Huanglongbing, grape downy mildew, strawberry gray mold etc. This innovation combines two ingredients (FZ and YC) with different modes of action, dramatically improving plant inducible acquired resistance. Therefore, this composition dramatically enhances the control efficacy of plant diseases caused by fungi, bacteria or virus, expands the antimicrobial spectrum and promotes the plant growth.