Abstract: An image processing method, an image processing device, a training method of a neural network, an image processing method based on a combined neural network model, a constructing method of a combined neural network model, a neural network processor, and a storage medium are provided. The image processing method includes: obtaining, based on an input image, initial feature images of N stages with resolutions from high to low, N is a positive integer and N>2; performing, based on initial feature images of second to N-th stages, cyclic scaling processing on an initial feature image of a first stage, to obtain an intermediate feature image; and performing merging processing on the intermediate feature image to obtain an output image. The cyclic scaling processing includes hierarchically-nested scaling processing of N?1 stages, and scaling processing of each stage includes down-sampling processing, concatenating processing, up-sampling processing, and residual link addition processing.

Abstract: The present disclosure provides use of Clostridium ghonii combined with a tumor angiogenesis inhibitor in preparing a pharmaceutical product for treating a tumor. The present disclosure further provides a drug for treating a tumor, where the drug includes active ingredients of Clostridium ghonii and a tumor angiogenesis inhibitor.

Abstract: The present invention relates to a composition, preparation and use thereof, and a product coated with the composition. The composition comprises: (a) a polyurethane polymer which is a reaction product comprising the following components: (a1) a polyisocyanate, (a2) a compound having an isocyanate-reactive group, which comprises a polymer polyol selected from one or more of the following: a polyether polyol and a polyolefin polyol, (a3) optionally an emulsifier, (a4) optionally a solvent, and (a5) optionally a reactive diluent; (b) an organic antioxidant in an amount of 0.01 wt % to 2.4 wt %, based on the total weight of solid components of the composition; (c) a chelating agent; and (d) water. The composition according to the present invention has good high-temperature yellowing resistance.

Abstract: The present invention relates to a composition, preparation and use thereof, and a product coated with the composition. The composition comprises: (a) a polyurethane polymer which is a reaction product comprising the following components: (a1) a polyisocyanate, (a2) a compound having an isocyanate-reactive group, which comprises a polyester polyol in an amount of more than 10 wt %, based on the total weight of the compound having an isocyanate-reactive group, (a3) optionally an emulsifier, (a4) optionally a solvent, and (a5) optionally a reactive diluent; (b) an organic antioxidant in an amount of 0.001 wt % to 1 wt %, based on the total weight of solid components of the composition; (c) a chelating agent; and (d) water. The composition according to the present invention has good yellowing resistance.

Abstract: There is disclosed a magnetically attractable short-range wireless personal area network speaker. In an embodiment, the speaker includes a loudspeaker, a control circuit board electrically connected to the loudspeaker, a battery, a speaker housing that includes a speaker body, a speaker bottom plate and a limiting part, and a magnet, as well as a microphone and/or a wireless charger. The limiting part may include an upper cavity at a bottom of the speaker body and a lower cavity at the bottom plate, and the magnet may be fixed the limiting part, outside a magnetic circuit range of the loudspeaker. The wireless charger may include a power pick-up unit (wireless charging receiving coil(s)), which may be disposed in the bottom plate, and a communications and control unit (a wireless charging receiving circuit board electrically connected to the battery and configured to regulate power to charge the battery). Other embodiments are also disclosed.

Abstract: The present disclosure relates to use of a Clostridium ghonii spore combined with pembrolizumab in cancer treatment. It is found for the first time that the Clostridium ghonii spore combined with pembrolizumab can significantly improve a curative effect of colon cancer and reduce a dose of the pembrolizumab, and thus is efficient and low-toxic. Oncolysis by Clostridium ghonii can affect immunogenicity of a tumor microenvironment (TME) by various ways, converts an immunosuppressive state of the TME into an immune-activated state, adjusts the immunosuppressive TME, and breaks an immune tolerance. An optimal combination of the Clostridium ghonii spore and the pembrolizumab thoroughly removes about 20% of mouse tumor tissues. A benefit range of patients with tumors treated by a PD-1 antibody is expanded. The combination even has an obvious curative effect on patients failed the treatment by the PD-1 antibody.

Abstract: An image processing method, an image processing device, a training method of a neural network, an image processing method based on a combined neural network model, a constructing method of a combined neural network model, a neural network processor, and a storage medium are provided. The image processing method includes: obtaining, based on an input image, initial feature images of N stages with resolutions from high to low, where N is a positive integer and N>2, performing, based on initial feature images of second to N-th stages, cyclic scaling processing on an initial feature image of a first stage, to obtain an intermediate feature image; and preforming merging processing on the intermediate feature image to obtain an output image. The cyclic scaling processing includes hierarchically-nested scaling processing of N?1 stages, and scaling processing of each stage includes down-sampling processing, concatenating processing, up-sampling processing, and residual link addition processing.

Abstract: A computer-implemented method is provided. The computer-implemented method includes rendering a dynamic effect to one or more objects in an image. The method includes setting boundary points surrounding a foreground object to define a boundary area in which a dynamic movement is to be realized; setting a movement line to define a dynamic movement direction along which the dynamic movement is to be realized, wherein setting the movement line includes detecting a continuous touch over different positions on the touch control display panel; setting a stationary area to define an area in which the dynamic movement is prohibited, wherein setting the stationary area includes detecting a first touch area corresponding to the stationary area on the touch control display panel; and generating an animation of the foreground object in the boundary area moving along the dynamic movement direction, thereby realizing the dynamic effect in the image.

Abstract: An image processing method and an image processing device are provided. The image processing method includes performing at least one of a scratch repairing step, a dead point repairing step, a denoising step and a color cast correcting step on a to-be-processed video frame. According to the embodiments of the present disclosure, it is able to repair a scratch and a dead point, remove a noise and/or correct color cast for a video frame, thereby to improve a display effect of the video frame.

Abstract: The present disclosure discloses a media monitoring method, apparatus and system. The method includes: obtaining image information of a program verification region in a display frame of a currently monitored display screen, wherein the program verification region is configured to display verification information corresponding to a current program that should be broadcast on the display screen; identifying the image information to determine actual display information representing a current actually-broadcast program; and performing verification on the actual display information according to the verification information, and determining that the display screen broadcasts normally if the verification is passed, or determining that the display screen does not broadcast normally if the verification is failed.

Abstract: Disclosed are an image processing method and device, a training method of a neural network and a storage medium. The image processing method includes: obtaining an input image, and processing the input image by using a generative network to generate an output image. The generate network includes a first sub-network and at least one second sub-network, and the processing the input image by using the generative network to generate the output image includes, processing the input image by using the first sub-network to obtain a plurality of first feature images; performing a branching process and a weight sharing process on the plurality of first feature images by using the at least one second sub-network to obtain a plurality of second feature images; and processing the plurality of second feature images to obtain the output image.

Abstract: The present disclosure provides an image processing method and an image processing apparatus. The image processing method includes: obtaining a to-be-converted SDR image; using a first convolutional network to perform feature analysis on the SDR image, to obtain N weights of the SDR image; where the N weights are respectively configured to characterize proportions of color information of the SDR image to color information characterized in preset N 3D lookup tables, the N 3D lookup tables are configured to characterize color information of different types; obtaining a first 3D lookup table for the SDR image according to the N weights and the N 3D lookup tables; using the first 3D lookup table to adjust the color information of the SDR image to obtain an HDR image; and using a second convolutional neural network to perform refinement correction on the HDR image to obtain an output image.

Abstract: The present disclosure discloses a method, apparatus and system for customer group analysis, and a storage medium. The method includes: obtaining video images of a customer group passing by a display apparatus; recognizing and tracking head images of the customer group in the video images, and determining behavior characteristics of individuals in the customer group; and performing statistical analysis on the behavior characteristics of the customer group corresponding to the display apparatus, so as to update a quantity of individuals corresponding to each behavior characteristic.

Abstract: A computer-implemented image-processing method is provided. The computer-implemented image-processing method includes obtaining a pair of training samples including a training image having a first degree of sharpness and a reference image having a second degree of sharpness, the second degree greater than the first degree, at least portions of the training image and the reference image in a same pair having same contents; inputting the training image to the image-enhancing convolutional neural network to generate a training enhanced image; inputting the training enhanced image into an edge detector; generating, by the edge detector, a plurality of first edge maps; inputting the reference image into the edge detector; generating, by the edge detector, a plurality of second edge maps; and tuning parameters in the image-enhancing convolutional neural network to minimize at least the one or more first losses and a second loss.

Abstract: A computer-implemented method using a convolutional neural network is provided. The computer-implemented method using a convolutional neural network includes processing an input image through at least one channel of the convolutional neural network to generate an output image including content features of the input image morphed with style features of a reference style image. The at least one channel includes a down-sampling segment, a densely connected segment, and an up-sampling segment sequentially connected together. Processing the input image through the at least one channel of the convolutional neural network includes processing an input signal through the down-sampling segment to generate a down-sampling segment output; processing the down-sampling segment output through the densely connected segment to generate a densely connected segment output; and processing the densely connected segment output through the up-sampling segment to generate an up-sampling segment output.

Abstract: Provided is a method for the treatment of a lymphoid malignant neoplasm in a subject in need thereof comprising administering to the subject an effective amount of a bispecific antibody which comprises a Fab portion that binds CD47 and a Fab portion that binds CD20. In some embodiments, the lymphoid malignant neoplasm is Non-Hodgkin's Lymphoma (NHL), follicular lymphoma (FL), diffuse large B-cell lymphoma (DLBCL), marginal zone lymphoma (MZL), mantle cell lymphoma (MCL), or primary mediastinal B-cell lymphoma. In certain embodiments, the lymphoid malignant neoplasm is NHL.

Abstract: The disclosure relates to an image processing method. The method may include: obtaining an image frame obtained through photographing and performing background separation on the image frame to obtain a subject frame and a background frame; obtaining a plurality of target background frames based on the background frame, in which the plurality of target background frames contain the same background content, and sizes of the background content in the plurality of target background frames are inconsistent; and synthesizing a target subject frame and the plurality of target background frames respectively to obtain a plurality of target image frames, and encoding the plurality of obtained target image frames into a video file, in which the target subject frame is one frame of an image in the subject frame.

Abstract: A video image de-interlacing method is provided. The method-includes: acquiring a single frame of original video image; extracting odd field data and even field data in an original video image; performing N-1 times of down-sampling on the odd field data to obtain N-1 odd field data with different resolutions and performing N-1 times of down-sampling on the even field data to obtain N-1 even field data with different resolutions; combining odd field data and even field data with the same resolution to obtain a down-sampled image; and inputting the original video image and the down-sampled image to the de-interlacing network for de-interlacing.

Abstract: An image restoration method and apparatus, and an electronic device. The method includes: inputting, into a target denoising network, an image to be processed, where the target denoising network includes a single-frame network and a recursive network, and the image to be processed is any frame in a video to be processed (S101); removing, via the single-frame network, compression noise of the image to be processed, and outputting a first image (S102); according to the content of the previous frame of image, removing, via the recursive network, compression noise of the image to be processed, and outputting a second image, where the previous frame of image is the previous frame of image of the image to be processed in the video to be processed (S103); and performing weighted summation on the first image and the second image, and outputting a denoised image for the image to be processed (S104).