Abstract: Examples of the present disclosure provide a method and an apparatus for denoising a low-light image, wherein the method includes: acquiring a low-light image in RAW domain; performing a preset image enhancement transformation on the low-light image in the RAW domain, and inputting the transformed image into a pre-trained denoising network model to obtain an output image; wherein, the denoising network model is trained based on sample images, and the sample images include a low-light image with simulated dead pixels and a noiseless image; performing an inverse transformation of the preset image enhancement transformation on the output image to obtain a denoised image. It can significantly reduce the influence of dead pixels of images on the process of denoising the low-light image and improve the quality of low-light image denoising.

Abstract: A fan includes a first blower and a second blower each having an impeller. The first blower includes a first motor and a first motor drive controller to control driving of the first motor and communicate with the second blower. The second blower includes a second motor and a second motor drive controller to control driving of the second motor and communicate with the first blower. The first motor drive controller controls the driving of the first motor based on a result of communication with the second blower.

Abstract: A shipping cover for a staple cartridge includes a body having an upper surface and a lower surface that is in close opposition to the staple cartridge when the shipping cover is secured to the staple cartridge. The shipping cover includes a latch that is received within a body of the staple cartridge to secure the shipping cover to the cartridge body. The latch is manually movable by a clinician to facilitate removal of the shipping cover from the staple cartridge.

Abstract: The embodiments of the present application provide a denoising method, apparatus, electronic device and medium, which relates to the technical field of image processing. The method comprises: inputting an image to be processed into an image denoising model, which is a model obtained by training a convolutional neural network model based on a preset training set, wherein the preset training set includes multiple groups of annotation data and sample data corresponding to each group of annotation data, and each group of annotation data includes multiple noiseless images obtained by performing motion simulation processing on one reference noiseless image, and the sample data corresponding to the group of annotation data includes images obtained by superimposing noise to the multiple noiseless images respectively; acquiring denoised image data output by the image denoising model; converting the image data into an image, to obtain a denoised image corresponding to the image to be processed.

Abstract: A product state quantification and remaining life prediction method, the method comprising: T1, acquiring design data and operating data of a product; T2, establishing a design model of the product on the basis of the design data, performing data fusion according to the design data and operating data to obtain a predicted performance curve of the product, and selecting an optimized operating state point in the predicted performance curve; and T3, establishing a cost model and an operating flexibility model of the product on the basis of the predicted performance curve, and calculating a remaining life prediction of the product according to a performance demand or operating cost of the product.

Abstract: Various embodiments of the teachings herein include a dynamic prediction control method for a precision air conditioner. An example method includes: generating a three-dimensional simulation model on the basis of a simulation template according to static information of a hardware configuration and layout of an application scene where the precision air conditioner is located, wherein the three-dimensional simulation model and a static model of the hardware configuration and layout of the application scene correspond to each other; running a simulation on the basis of a dynamic parameter of the precision air conditioner corresponding to the three-dimensional simulation model and establishing a correspondence relationship between the dynamic parameter and a simulation result using machine learning, so as to generate a proxy model; and predicting a temperature distribution and change of the application scene on the basis of the proxy model and real-time dynamic data of the precision air conditioner.

Abstract: An antenna device includes a plurality of dipole antennas and a port. Each of the dipole antennas is connected to the port. The plurality of dipole antennas is arranged around the port. Each of the plurality of dipole antennas includes two ends. The ends of the dipole antennas are arranged in a plurality of pairs. Each pair includes one end of one of the dipole antennas and one end of another one of the dipole antennas. The two ends in each pair are arranged in proximity to each other. One or more switches are configured to switch between (1) an omnidirectional state, in which the ends of the dipole antennas are not connected to each other; and (2) a directional state, in which the two ends in each of one or more of the pairs are connected to each other.

Abstract: A method and an apparatus for generating image data, which relate to the technical field of image processing. The method comprises: obtaining a first pixel value of each pixel in a first image based on original pixel values of the first image acquired by an image acquisition device when ambient light brightness is greater than a first preset brightness threshold; obtaining a second pixel value of each pixel by dividing the first pixel value of this pixel by a preset multiple; the second preset brightness threshold is less than the first preset brightness threshold; obtaining a third pixel value of each pixel by adding Poisson noise based on a total system gain of the image acquisition device on the basis of the second pixel value of this pixel; generating original pixel values of a target image which corresponds to the first image for which the ambient light brightness is less than the second preset brightness threshold based on respective third pixel values.

Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.

Abstract: A reconfigurable antenna includes a bottom plate, a vertically polarized high-density antenna, and a controllable reflector. The controllable reflector is located between the bottom plate and the vertically polarized high-density antenna, and a projection of the controllable reflector on the bottom plate is at a center of a projection of the vertically polarized high-density antenna on the bottom plate. The controllable reflector includes a switch, and the switch is configured to enable the controllable reflector to be in an operating state or an off state.

Abstract: An antenna has a reflector and an active element. The reflector includes a multi-segment metal structure having a length within a first value range. The multi-segment metal structure includes a first metal structure connected to a second metal structure. A PIN diode is disposed on the first metal structure. The first metal structure is parallel to a polarization direction of the active element. The second metal structure is perpendicular to the first metal structure.

Abstract: An automated checkout system modifies received images of machine-readable labels to improve the performance of a label detection model that the system uses to decode item identifiers encoded in the machine-readable labels. For example, the automated checkout system may transform subregions of an image of a machine-readable label to adjust for distortions in the image's depiction of the machine-readable label. Similarly, the automated checkout system may identify readable regions within received images of machine-readable labels and apply a label detection model to those readable regions. By modifying received images of machine-readable labels, these techniques improve on existing computer-vision technologies by allowing for the effective decoding of machine-readable labels based on real-world images using relatively clean training data.

Abstract: An automated checkout system modifies received images of machine-readable labels to improve the performance of a label detection model that the system uses to decode item identifiers encoded in the machine-readable labels. For example, the automated checkout system may transform subregions of an image of a machine-readable label to adjust for distortions in the image's depiction of the machine-readable label. Similarly, the automated checkout system may identify readable regions within received images of machine-readable labels and apply a label detection model to those readable regions. By modifying received images of machine-readable labels, these techniques improve on existing computer-vision technologies by allowing for the effective decoding of machine-readable labels based on real-world images using relatively clean training data.

Abstract: A method and an apparatus for generating image data, which relate to the technical field of image processing. The method comprises: obtaining a first pixel value of each pixel in a first image based on original pixel values of the first image acquired by an image acquisition device when ambient light brightness is greater than a first preset brightness threshold; obtaining a second pixel value of each pixel by dividing the first pixel value of this pixel by a preset multiple; the second preset brightness threshold is less than the first preset brightness threshold; obtaining a third pixel value of each pixel by adding Poisson noise based on a total system gain of the image acquisition device on the basis of the second pixel value of this pixel; generating original pixel values of a target image which corresponds to the first image for which the ambient light brightness is less than the second preset brightness threshold based on respective third pixel values.

Abstract: An antenna for wireless communications includes a horizontal polarization antenna and a vertical polarization antenna that are disposed in a stacked manner. The horizontal polarization antenna includes a radiation element and a double-sided parallel strip line. One end of the double-sided parallel strip line is connected to the radiation element. A length range of the double-sided parallel strip line is 0.58 to 1.35 times a waveguide wavelength of an electromagnetic wave in the double-sided parallel strip line at an operating frequency of the vertical polarization antenna.

Abstract: An antenna device includes a plurality of dipole antennas and a port. Each of the dipole antennas is connected to the port. The dipole antennas are arranged around the port. Each of the dipole antennas comprises two ends. The device further includes a plurality of passive elements. The ends of the dipole antennas and the passive elements are interchangeably arranged around the port such that each of the passive elements is situated between ends of two different antennas from the plurality of dipole antennas. One or more switches are configured to switch between an omnidirectional state, in which the ends of the dipole antennas are not connected to the plurality of passive elements, and a directional state, in which at least one end of one of the passive elements is connected to at least one end of one of the antennas.

Abstract: An automated checkout system accesses an image of an item inside a shopping cart and a location of the shopping cart within a store. The automated checkout system identifies a set of candidate items located within a threshold distance of the location of the shopping cart based on an item map. The item map describes a location of each item within the store and the location of each candidate item corresponds to a location of the candidate item on the item map. The automated checkout system inputs visual features of the item extracted from the image to a machine-learning model to identify the item by determining a similarity score between the item and each candidate item of the set of candidate items. After identifying the item, the automated checkout system displays a list comprising the item and additional items within the shopping cart to a user.

Abstract: The present application disclosures a double production line and a rapid prefabrication process of a segmental beam. The double production line including two production machine and a track system provided on the construction ground; the production machine includes a fixed end mold, two side molds, a bottom mold trolley, a middle internal mold trolley and two side internal mold trolley; two side molds are positioned on two sides of the fixed end mold respectively, the fixed end mold and two side molds together define a pouring position with an end opening, two openings of the pouring position are arranged facing each other; the track system includes a transverse track and a longitudinal track communicated with each other, two pouring positions are both positioned in the extension path of the transverse track, and the longitudinal track is positioned between two pouring positions.

Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.

Abstract: A fan includes a first blower and a second blower each having an impeller. The first blower includes a first motor and a first motor drive controller to control driving of the first motor and communicate with the second blower. The second blower includes a second motor and a second motor drive controller to control driving of the second motor and communicate with the first blower. The first motor drive controller controls the driving of the first motor based on a result of communication with the second blower.