Abstract: Disclosed is a bubbling humidifier suitable for high-flow fuel cell test equipment, comprising an upper and lower tank, an aeration device and an anti-boiling device; wherein the upper tank and the lower tank are connected and the aeration device and the anti-boiling device are arranged inside the tank. The present disclosure adopts a bubbling humidifier suitable for a high-flow rate fuel cell test equipment, which uses circulating water to complete humidification of gas. effectively improving humidification while reducing humidifier dimensions, lowering production costs, and facilitating widespread adoption; the design of water inlet and water outlet pipelines slows down the flow of circulating water in the tank, reduces the disturbance of circulating water to gas, and improves the stability of the humidifier; the design of the anti-boiling device effectively prevents the water from rushing out of the tank when the gas flow rate is too high.

Abstract: A method comprises: obtaining, by a source terminal, first media data of a real person and comprising a first video or a first audio of the real person; extracting, by the source terminal and from the first media data, feature data for describing the real person and comprising a facial feature, a morphological feature, or a voice feature of the real person, wherein the facial feature and the morphological feature are from the first video, and wherein the voice feature is from the first audio; sending, by the source terminal and to a cloud server, the feature data; generating, by the cloud server and based on the feature data and a multimodal AI-driven model, second media data of a digital human and comprising a second video or a second audio of the digital human; and sending, by the cloud server and to a destination terminal, the second media data.

Abstract: A watermark embedding and extraction method, and an electronic device are provided. The method includes: obtain a plurality of original videos corresponding to a same video content, and a video serial number and a to-be-embedded watermark corresponding to each of the plurality of original videos; for each of the plurality of original videos, dividing the original video according to a first quantity and a second quantity to obtain a frame sequence of the original video; allocating a watermark code for each of the frame sequences according to a timing of each of the frame sequences and an order of each watermark code, and determining a first watermark and a second watermark corresponding to each of the frame sequences according to the watermark code allocated to each of the frame sequences; and adding a target watermark for each sub-unit to obtain a watermark video corresponding to the original video.

Abstract: The present disclosure provides an interface access processing method and apparatus, a computer device and a storage medium, and the method includes: acquiring target access behavior sequences of an access party within a first specified time range, the target access behavior sequences including an access action behavior sequence and an access time interval sequence; calling an identification model for prediction processing to obtain an identification result based on the access action sequence and the access time interval sequence, the identification result being used for representing a classification probability that the access party has abnormal behaviors; and controlling an interface access request within a second specified time range of the access party according to the identification result, a start time of the second specified time range being later than an end time of the first specified time range.

Abstract: The present disclosure provides an interface access processing method and apparatus, a computer device and a storage medium, and the method includes: acquiring target access behavior sequences of an access party within a first specified time range, the target access behavior sequences including an access action behavior sequence and an access time interval sequence; calling an identification model for prediction processing to obtain an identification result based on the access action sequence and the access time interval sequence, the identification result being used for representing a classification probability that the access party has abnormal behaviors; and controlling an interface access request within a second specified time range of the access party according to the identification result, a start time of the second specified time range being later than an end time of the first specified time range.

Abstract: The application discloses a virtual human video generation method and apparatus. The method includes: obtaining a driving text; obtaining, based on the driving text and an action annotation of a first video, an action type corresponding to the driving text, where the action annotation includes a plurality of action types of a character in the first video; extracting, from the first video based on the action type, an action representation corresponding to the driving text; and generating a virtual human video based on the action representation. According to this application, the virtual human video in which the action of the character is accurate, controllable, and compliant with a preset action specification can be automatically generated, and personalized customization of an action of a virtual human can be implemented by adjusting the action specification.

Abstract: The present disclosure relates to an image processing method, readable medium and electronic device. The method comprises: acquiring a watermark image, wherein the watermark image is an image embedded with a foreground watermark, and the foreground watermark is generated by watermark information; determining a first image channel embedded with the foreground watermark and a second image channel not embedded with the foreground watermark in the watermark image, and determining a channel difference feature map of the watermark image according to channel information of the first image channel and channel information of the second image channel; performing feature enhancement processing on the channel difference feature map to obtain a first watermark enhanced feature map of the watermark image, wherein the first watermark enhanced feature map is used for extracting the watermark information of the watermark image.

Abstract: The disclosure provides an LED light source recognition method, device, apparatus, and medium based on deep learning, belonging to the field of indoor positioning and navigation technology. The method includes the following. In an LED lighting environment, a spline frame is obtained through a CMOS camera, in which the spline frame is an image having dark stripes. The spline frame is input to a target detection model, a dark stripe detection result output by the target detection model is obtained. The multiple rectangular boxes are preprocessed, and based on the predicted classification corresponding to each preprocessed rectangular box, an image feature encoding sequence of the spline frame is determined. The image feature encoding sequence is compared with a light source feature encoding sequence corresponding to each LED light source to determine the light source feature encoding sequence that best matches the spline frame.

Abstract: A rendering model training method and apparatus are provided. A related video rendering method and apparatus, a device, and a storage medium are also provided. The rendering model training method includes: obtaining a first video including a face of a target object; mapping a facial action of the target object in the first video based on a three-dimensional face model, to obtain a second video including a three-dimensional face; and training an initial rendering model by using the second video as an input of the initial rendering model and using the first video as supervision of an output of the initial rendering model, to obtain a target rendering model. The second video generated based on the three-dimensional face model is used as a sample for training the rendering model.

Abstract: In a model training method, a computing device generates an initial virtual human speaking video based on an audio data set and a person speaking video. The computing device trains a lip synchronization parameter generation model based on the audio data set and a lip synchronization training parameter used as a model training label. The computing device then uses the lip synchronization parameter generation model to generate a lip synchronization parameter based on input audio, and the lip synchronization parameter is used to drive a virtual human to speak. The computing device expands a data amount of the lip synchronization training parameter by using the initial virtual human speaking video.

Abstract: The present disclosure relates to an image processing method, readable medium and electronic device. The method comprises: acquiring a watermark image, wherein the watermark image is an image embedded with a foreground watermark, and the foreground watermark is generated by watermark information; determining a first image channel embedded with the foreground watermark and a second image channel not embedded with the foreground watermark in the watermark image, and determining a channel difference feature map of the watermark image according to channel information of the first image channel and channel information of the second image channel; performing feature enhancement processing on the channel difference feature map to obtain a first watermark enhanced feature map of the watermark image, wherein the first watermark enhanced feature map is used for extracting the watermark information of the watermark image.

Abstract: A generation method and apparatus for sample data, a method and apparatus for information detection, a device and a storage medium are provided, and the generation method includes: acquiring first reference data, the first reference data including target information matching a target information type, and the target information type being a preset information type with a security requirement; performing analysis processing on the target information in the first reference data to generate an analysis result corresponding to the target information, the analysis processing including semantic analysis, lexical structure analysis and grammatical structure analysis; generating a plurality of positive sample information and a plurality of negative sample information based on the analysis result corresponding to the target information; generating a sample data set including positive sample data and negative sample data based on the plurality of positive sample information, the plurality of negative sample information

Abstract: Embodiments of the disclosure relate to a method, apparatus, device and storage medium for watermark embedding and watermark extraction. The watermark embedding method includes: determining, based on a set of key points identified in an image to be processed, at least one image block to be processed in the image to be processed; generating, based on watermark information and the at least one image block to be processed, at least one target image block corresponding to the at least one image block to be processed respectively, each target image block being embedded with at least a portion of the watermark information; and generating a target image for the image to be processed by replacing the at least one image block to be processed with the at least one target image block in the image to be processed respectively.

Abstract: A method and apparatus for sample generation, a method and apparatus for information detection, a computer device, and a storage medium are provided, and the method for sample generation includes: acquiring a reference data set, where the reference data set includes first reference data and second reference data, the first reference data includes at least one information sample value, the information sample value belongs to a target information type, and the second reference data does not include an information sample value of the target information type; determining a target template corresponding to the first reference data based on the at least one information sample value in the first reference data; generating a plurality of sample information based on the target template corresponding to the first reference data; and generating a sample data set based on the plurality of sample information and the second reference data.

Abstract: A method and apparatus for watermark extraction, a computer device and a storage medium are provided. The method includes: acquiring an image to be detected; inputting the image to be detected into a watermark recognition network and acquiring a watermark detection result corresponding to the image to be detected; and when the watermark detection result includes presence of a hidden watermark, extracting the hidden watermark in the image to be detected based on at least one extraction algorithm corresponding to the watermark detection result.

Abstract: An application page development method includes a static page of a target application being first obtained, and then an application page including an interaction function corresponding to interaction description information being generated based on the interaction description information input by a user and the static page. In other words, the application page has a function of interacting with the user.

Abstract: A sound absorber unit and a vehicle wheel having a sound absorber device are provided. The sound absorber devices includes at least one sound absorber unit or at least one sound absorber assembly which is composed of a plurality of sound absorber units. The sound absorber unit is constructed into a box body in a hexahedron shape and forms a three-layer Helmholtz resonance sound absorption structure with double holes and single holes combined, and meanwhile, the sound absorber unit or the sound absorber assembly forms a structural resonance sound absorber. The double-absorption wheel air chamber sound resonance function organically combining Helmholtz resonance sound absorption and structural resonance sound absorption can be realized.

Abstract: A sound absorber is configured as a rectangular hexahedral box and forms a porous double-layer Helmholtz resonance sound absorbing structure, at the same time, the sound absorber in the form of a box forms a structural resonance sound absorbing device itself, and the first-order natural mode frequency of the device is identical to that of a wheel air chamber. When the box-type sound absorbing structure is assembled in a wheel, double functions of absorbing acoustic resonance of the wheel air chamber under the organic combination of Helmholtz resonance sound absorption and structural resonance sound absorption can be realized.

Abstract: A method for generating a video corpus is provided, and specifically includes: obtaining a video to be processed, where the video to be processed corresponds to voice content, and some video images of the video to be processed include a subtitle corresponding to the voice content; and obtaining, based on the voice content, a target video clip from the video to be processed, and using a subtitle included in a video image in the target video clip as an annotation text of the target video clip, to obtain a video corpus. In this way, the video corpus can be automatically generated. Impact on segmentation precision caused by a subjective cognitive error in a manual annotation process can be avoided. Further, efficiency of generating the video corpus is generally high.

Abstract: A high-precision intelligent centering device, consisting of a symmetrical synchronous centering mechanism. The invention can meet the needs of wheel centering in use with the ideal effect and high efficiency. Work is safe and reliable, degree of automation is high, and it is especially suitable for mass production on the production line.