Abstract: An image processing method comprises obtaining an input image; converting the input image or a feature map of the input image into a plurality of target input images or target feature maps, wherein a resolution of each of the target input images or the target feature maps is smaller than a resolution of the feature map of the input image or the input image, and pixels at the same position in each of the target input images or the target feature maps are of a neighborhood relationship with the input image or the feature map of the input image; processing at least a part of the plurality of target input images or target feature maps by one or more convolution blocks in a convolutional neural network; and increasing a resolution of a feature map output from the one or more convolution blocks in the convolutional neural network.

Abstract: A device for detecting a slot wedge, an air gap and a broken rotor bar is provided, where a sequential circuit generates double concurrent pulses; the sequential circuit is connected to driving power modules; the driving power modules are connected to front-end interface circuits; the front-end interface circuits convert the double concurrent pulses into corresponding magnetic-field pulses; the magnetic-field pulses are transmitted to power supply terminals on adjacent phases of stator windings through impedance matching pins and coupled at a corresponding coil, air gap and squirrel cage rotor to generate single groups of cyclic rotating magnetic potentials; single rotating magnetic potentials are sequentially generated in adjacent slots on each of the phases of the stator windings; rotating electric potentials in magnetic circuits with two symmetrical phases are magnetically coupled to form distributed coupling magnetic field reflected full-cycle waves for reflecting a difference of a corresponding slot wedg

Abstract: The present disclosure provides more efficient techniques for removing a host from a multi-host database system. An instruction to remove a host system may be received. In response, a determination of whether the first host system does or does not store any source tables is made based on a host-type identifier for the host system. This determination may not require obtaining landscape information for each of the hosts in the database system. If the host system stores replica tables and does not store source tables, those replica tables may be dropped based on the determination that the first host system does not store any source tables. As such, in cases where table redistribution is not needed the landscape information is not obtained, thereby making the host removal process more efficient.

Abstract: A method of utilizing humic acid to prepare layered humic acid/manganese oxide composite catalyst and its application, the method includes the steps of: adding sodium hypochlorite, manganese salt and humic acid to a water source, stirring and mixing; then introducing into a filter device having a filter material of manganese and a support medium, and generating a layered humic acid/manganese oxide composite catalyst on a surface of the filter material while directing a continuous water flow of the water source into the filter device with a short empty bed contact time for a short time. The catalyst can be used to effectively remove manganese to maintain an effluent with a Mn2+ concentration of not more than 20 ?g/L and to effectively remove heavy metals such as iron, manganese, arsenic, thallium, molybdenum or lead from the water source under neutral, acidic or alkaline conditions with a removal rate of 95% more.

Abstract: A duchenne muscular dystrophy-related exonic splicing enhancer, sgRNA and gene editing tool can be applied in the preparation of drugs for treating duchenne muscular dystrophy. The gene editing tool designed on the basis of cytosine deaminase AID mutants and Cas9 mutants can perform site-specific modification on a mammalian genome by using an adeno-associated virus (AAV) as a vector. By optimizing an encoding nucleic acid sequence and an element composition structure of the editing tool, site-specific targeted modification of mammalian genetic material DNA can be efficiently achieved; and by performing targeted genetic manipulation on the nucleic acid sequence carrying disease mutations, a pathogenic mutation cannot be retained in a mature protein amino acid sequence or the pathogenic mutation cannot perform its function, so that the purpose of treating various gene mutation type genetic rare diseases is achieved, and the advantages of high efficiency, safety and stability are achieved.

Abstract: The coastal ecosystem carbon pool estimation method of the invention belongs to the field of environmental assessment, and includes the following steps: (a) determining the spatial boundary of the coastal ecosystem; (b) determining the dominant plant classification area of the coastal ecosystem; (c) calculating the carbon source of the freshwater plant dominant area; (d) size setting of carbon source sampling point in coastal ecosystem; (e) sampling method of carbon source sampling point in coastal ecosystem; (f) carbon source estimation method in coastal ecosystem.

Abstract: The present disclosure provides a method and apparatus for facial classification, which is applied to the field of image processing. The method includes acquiring a color image of a target face, where the color image includes information of at least one channel, inputting the information into a neural network, and classifying, by the neural network, the target face according to the information and a first parameter. The first parameter includes at least one facial category and first parameter data for identifying a facial category of the target face. The method and device of the present disclosure can analyze facial attributes from the content of a facial image, and automatically classify many facial images according to their facial attributes. This reduces the burden of manual classification, thereby allowing facial images to be stored in a clear and orderly fashion and improving classification efficiency.

Abstract: An image processing method comprises obtaining an input image; converting the input image or a feature map of the input image into a plurality of target input images or target feature maps, wherein a resolution of each of the target input images or the target feature maps is smaller than a resolution of the feature map of the input image or the input image, and pixels at the same position in each of the target input images or the target feature maps are of a neighborhood relationship with the input image or the feature map of the input image; processing at least a part of the plurality of target input images or target feature maps by one or more convolution blocks in a convolutional neural network; and increasing a resolution of a feature map output from the one or more convolution blocks in the convolutional neural network.

Abstract: The present disclosure provides a method and apparatus for expression recognition, which is applied to the field of image processing. The method includes acquiring a three-dimensional image of a target face and a two-dimensional image of the target face, where the three-dimensional image includes first depth information of the target face and first color information of the target face, and the two-dimensional image includes second color information of the target face. A first neural network classifies an expression of the target face according to the first depth information, the first color information, the second color information, and a first parameter to the target face. The first parameter includes at least one facial expression category and first parameter data for identifying an expression category of the target facial. The disclosed method and device can accurately recognize facial expressions under different facial positions and different illumination conditions.

Abstract: A method of establishing person image attribute model, including: obtaining face detection data and determining face regions of interest; randomly labeling person image attributes of some of the face regions of interest to obtain a training sample; training a person image attribute model according to the training sample; and optimizing the trained person image attribute model to obtain an optimized person image attribute model through an active learning algorithm, according to an unlabeled sample set as output by a trained person image attribute model.

Abstract: The present disclosure provides a method and apparatus for expression recognition, which is applied to the field of image processing. The method includes acquiring a three-dimensional image of a target face and a two-dimensional image of the target face, where the three-dimensional image includes first depth information of the target face and first color information of the target face, and the two-dimensional image includes second color information of the target face. A first neural network classifies an expression of the target face according to the first depth information, the first color information, the second color information, and a first parameter to the target face. The first parameter includes at least one facial expression category and first parameter data for identifying an expression category of the target facial. The disclosed method and device can accurately recognize facial expressions under different facial positions and different illumination conditions.

Abstract: The present disclosure provides a method and apparatus for facial classification, which is applied to the field of image processing. The method includes acquiring a color image of a target face, where the color image includes information of at least one channel, inputting the information into a neural network, and classifying, by the neural network, the target face according to the information and a first parameter. The first parameter includes at least one facial category and first parameter data for identifying a facial category of the target face. The method and device of the present disclosure can analyze facial attributes from the content of a facial image, and automatically classify many facial images according to their facial attributes. This reduces the burden of manual classification, thereby allowing facial images to be stored in a clear and orderly fashion and improving classification efficiency.

Abstract: The present disclosure provides a method and apparatus for expression recognition, which is applied to the field of image processing. The method includes acquiring a three-dimensional image of a target face and a two-dimensional image of the target face, where the three-dimensional image includes first depth information of the target face and first color information of the target face, and the two-dimensional image includes second color information of the target face. A first neural network classifies an expression of the target face according to the first depth information, the first color information, the second color information, and a first parameter to the target face. The first parameter includes at least one facial expression category and first parameter data for identifying an expression category of the target facial. The disclosed method and device can accurately recognize facial expressions under different facial positions and different illumination conditions.

Abstract: The present disclosure provides a method and apparatus for facial classification, which is applied to the field of image processing. The method includes acquiring a color image of a target face, where the color image includes information of at least one channel, inputting the information into a neural network, and classifying, by the neural network, the target face according to the information and a first parameter. The first parameter includes at least one facial category and first parameter data for identifying a facial category of the target face. The method and device of the present disclosure can analyze facial attributes from the content of a facial image, and automatically classify many facial images according to their facial attributes. This reduces the burden of manual classification, thereby allowing facial images to be stored in a clear and orderly fashion and improving classification efficiency.

Abstract: A multi-nozzle combined atomizing dust suppression experimental equipment under the effect of airflow disturbance includes a simulated roadway device, water spray based dust suppression device and nozzle position adjustor. The simulated roadway device includes an inlet portion, front divergent portion, simulated roadway body, rear convergent portion and outlet portion. The water spray based dust suppression device includes a dust generation and extraction system and spraying system. The dust generation and extraction system includes a dust generation device, exhaust air duct, exhaust fan and outlet air duct while the spraying system includes a water tank, high pressure water pump, confined water pipe, pressure water flow converter and multiple nozzles. The nozzle position adjustor includes a nozzle slide, slide fixing rod, nozzle sliding rack and electrically-controlled drive system which controls the change of horizontal position and vertical position of the nozzles.

Abstract: A multi-nozzle combined atomizing dust suppression experimental equipment under the effect of airflow disturbance includes a simulated roadway device, water spray based dust suppression device and nozzle position adjustor. The simulated roadway device includes an inlet portion, front divergent portion, simulated roadway body, rear convergent portion and outlet portion. The water spray based dust suppression device includes a dust generation and extraction system and spraying system. The dust generation and extraction system includes a dust generation device, exhaust air duct, exhaust fan and outlet air duct while the spraying system includes a water tank, high pressure water pump, confined water pipe, pressure water flow converter and multiple nozzles. The nozzle position adjustor includes a nozzle slide, slide fixing rod, nozzle sliding rack and electrically-controlled drive system which controls the change of horizontal position and vertical position of the nozzles.

Abstract: A multi-nozzle combined atomizing dust suppression experimental equipment under the effect of airflow disturbance includes a simulated roadway device, water spray based dust suppression device and nozzle position adjustor. The simulated roadway device includes an inlet portion, front divergent portion, simulated roadway body, rear convergent portion and outlet portion. The water spray based dust suppression device includes a dust generation and extraction system and spraying system. The dust generation and extraction system includes a dust generation device, exhaust air duct, exhaust fan and outlet air duct while the spraying system includes a water tank, high pressure water pump, confined water pipe, pressure water flow converter and multiple nozzles. The nozzle position adjustor includes a nozzle slide, slide fixing rod, nozzle sliding rack and electrically-controlled drive system which controls the change of horizontal position and vertical position of the nozzles.

Abstract: A method for detecting a facial expression and repairing a smile face of a portrait photo includes the steps of: detecting a location and a range of a mouth region in an inputted portrait photo; capturing a patch in the mouth region and a predetermined peripheral range thereof; executing a comparison process to a smile state or a stiff state of the mouth region in the patch by a mouth state classifier; executing a calculation process to a repaired region of the mouth region when the mouth region is determined to be in the stiff state, in order to calculate a location of a plurality of feature points in the repaired region of the mouth region; and executing an image warping process to the location of the feature points and adjacent pixels thereof, for generating a portrait photo showing a smile state.

Abstract: The present invention is to provide a method of restoring closed-eye portrait photo, which comprises the steps of detecting the locations and range of the eyes of a portrait photo being taken, retrieving a patch of a designated range of the eyes area and its neighboring area which represents the expression of the eyes and its neighboring area, determining whether the eyes of said patch are open or closed by using an eyes state classifier, temporarily storing said patch as an open-eye templet when it is determined that the eyes are open, detecting the locations and range of the eyes of a subsequently taken portrait photo, calculating an eyes restoration area when it is determined that the eyes are closed, replacing the closed-eye patch with said open-eye templet, and performing fusion operation toward said eyes restoration area to ensure that each portrait photo generated is with the eyes opened.

Abstract: A method for detecting a facial expression and repairing a smile face of a portrait photo includes the steps of: detecting a location and a range of a mouth region in an inputted portrait photo; capturing a patch in the mouth region and a predetermined peripheral range thereof; executing a comparison process to a smile state or a stiff state of the mouth region in the patch by a mouth state classifier; executing a calculation process to a repaired region of the mouth region when the mouth region is determined to be in the stiff state, in order to calculate a location of a plurality of feature points in the repaired region of the mouth region; and executing an image warping process to the location of the feature points and adjacent pixels thereof, for generating a portrait photo showing a smile state.