Abstract: Provided are an image processing method and apparatus, a device, and a storage medium, relating to the technical field of image processing, in particular to the artificial intelligence fields such as computer vision and deep learning. The specific implementation scheme is as follows: inputting a to-be-processed image into an encoding network to obtain a basic image feature, wherein the encoding network includes at least two cascaded overlapping encoding sub-networks which perform encoding and fusion processing on input data at at least two resolutions; and inputting the basic image feature into a decoding network to obtain a target image feature for pixel point classification, wherein the decoding network includes at least one cascaded overlapping decoding sub-network to perform decoding and fusion processing on input data at at least two resolutions respectively.

Abstract: A digital-to-analog converter (DAC) includes a plurality of DAC cells, a mismatch error sorting circuit, and a dynamic element matching (DEM) circuit. The mismatch error sorting circuit generates a sorting result of the plurality of DAC cells according to mismatch error levels of the plurality of DAC cells. The DEM circuit shapes the mismatch error levels of the plurality of DAC cells according to the sorting result of the plurality of DAC cells.

Abstract: The present disclosure provides an object pose obtaining method, and an electronic device, relates to technology fields of image processing, computer vision, and deep learning. A detailed implementation is: extracting an image block of an object from an image, and generating a local coordinate system corresponding to the image block; obtaining 2D projection key points in an image coordinate system corresponding to a plurality of 3D key points on a 3D model of the object; converting the 2D projection key points into the local coordinate system to generate corresponding 2D prediction key points; obtaining direction vectors between each pixel point in the image block and each 2D prediction key point, and obtaining a 2D target key point corresponding to each 2D predication key point based on the direction vectors; and determining a pose of the object according to the 3D key points and the 2D target key points.

Abstract: A bidirectional DC-DC converter with three or more ports is described along with a method of operation thereof. The converter utilizes a common transformer for all ports and allows for power transfer from any port to any or all of the remaining ports. The converter may utilize a controller which implements variable-frequency control, delay-time control, and/or phase-delay control to achieve power transfer as desired between the converter ports. In some cases, power transfer between ports can operate similar to a series-resonant converter or a dual active bridge converter.

Abstract: Disclosed herein is an automated process of identifying shut-in parameters of a hydraulic fracturing operation from hydraulic fracturing treatment (HF) data. Also disclosed is a system and computer program product for automatically determining shut-in parameters from HF data. The HF data can be collected in real time during a HF from various sensors, equipment, or systems typically used in HFs or present at a well site. In one example, a method for automatically determining hydraulic fracturing parameters includes: (1) obtaining HF data, (2) determining a Rate Shut-In (RSI) time from the HF data, (3) determining a Well Shut-In (WSI) time using the RSI, and (4) calculating an Instantaneous Shut-In Pressure (ISIP) value based upon both the RSI and the WSI times, wherein determining the RSI time, the WSI time and calculating the ISIP value are automatically performed by one or more processors.

Abstract: A method and an apparatus for calibrating an external parameter of a camera are provided.

Abstract: A vehicle information detection method, a method for training a detection model, an electronic device and a storage medium are provided, and relates to the technical field of artificial intelligence, in particular to the technical field of computer vision and deep learning. The method includes: performing a first target detection operation based on an image of a target vehicle, to obtain a first detection result for target information of the target vehicle; performing an error detection operation based on the first detection result, to obtain error information; and performing a second target detection operation based on the first detection result and the error information, to obtain a second detection result for the target information.

Abstract: A startup control method for a DC/DC converter is used for starting the DC/DC converter with energy transferred from a low-voltage side to a high-voltage side, and includes: acquiring a voltage spike measurement value of a power switch at the low-voltage side; determining a duty cycle or a frequency of a driving signal according to the voltage spike measurement value and a preset voltage; and outputting the driving signal to a power switch at the high-voltage side, thereby charging a clamping capacitor of the power switch at the low-voltage side. The startup control method for a DC/DC converter of the disclosure can improve a reverse charging power of the converter to the maximum extent and reduce the time needed for charging a bus capacitor during a reverse startup process while ensuring voltage stress on the power switch not to exceed a limit.

Abstract: A voltage spike measurement circuit for a power switch includes a rectifier unit, a capacitive divider unit and a discharge unit, the rectifier unit configured to receive a voltage signal at both ends of a power switch and output a rectified signal; the capacitive divider unit includes at least two capacitors connected in series and configured to receive the rectified signal, divide the rectified signal based on a capacitance ratio of the at least two capacitors, and output a divider signal to a digital signal processor to calculate a voltage spike measurement value of the power switch; and the discharge unit connected in parallel to the capacitive divider unit.

Abstract: Embodiments of the present disclosure provide, among other implementations, sequence determining methods. One example method provides a sequence group, and one sequence group number is corresponding to at least two sequences, where one sequence is used for mapping to consecutive subcarriers, and at least one other sequence is used for mapping to equally-spaced subcarriers. In some embodiments of the present disclosure, as high as possible cross-correlation between a sending signal obtained after equally-spaced mapping is performed on a sequence in a sequence group can be determined, and a sending signal obtained after continuous mapping is performed on another sequence in the group.

Abstract: An image rendering method includes the steps below. A model of an environmental object is rendered to obtain an image of the environmental object in a target perspective. An image of a target object in the target perspective and a model of the target object are determined according to a neural radiance field of the target object. The image of the target object is fused and rendered into the image of the environmental object according to the model of the target object.

Abstract: A human body identification method, an electronic device and a storage medium, related to the technical field of artificial intelligence such as computer vision and deep learning, are provided. The method includes: inputting an image to be identified into a human body detection model, to obtain a plurality of preselected detection boxes; identifying a plurality of key points from each of the preselected detection boxes respectively according to a human body key point detection model, and obtaining a key point score of each of the key points; determining a target detection box from each of the preselected detection boxes, according to a number of the key points whose key point scores meet a key point threshold; and inputting the target detection box into a human body key point classification model, to obtain a human body identification result for the image to be identified.

Abstract: A normal distributions transform (NDT) method for LiDAR point cloud localization in unmanned driving is provided. The method proposes a non-recursive, memory-efficient data structure occupation-aware-voxel-structure (OAVS), which speeds up each search operation. Compared with a tree-based structure, the proposed data structure OAVS is easy to parallelize and consumes only about 1/10 of memory. Based on the data structure OAVS, the method proposes a semantic-assisted OAVS-based (SEO)-NDT algorithm, which significantly reduces the number of search operations, redefines a parameter affecting the number of search operations, and removes a redundant search operation. In addition, the method proposes a streaming field-programmable gate array (FPGA) accelerator architecture, which further improves the real-time and energy-saving performance of the SEO-NDT algorithm. The method meets the real-time and high-precision requirements of smart vehicles for three-dimensional (3D) lidar localization.

Abstract: Radar transmissive pigments, coatings, films, articles, method of manufacture thereof, and methods of use thereof are provided. The pigment comprises a non-conductive composite. The non-conductive composite comprises a semiconductor and/or a dielectric, and a metal dispersed in and/or on the semiconductor and/or dielectric. The pigment has an aspect ratio of at least 5 as measured by the Aspect Ratio Test.

Abstract: A magnetic component includes a magnetic core and a first winding module. The magnetic core has two opposite openings and at least one magnetic column. The first winding module has a plurality of annular metal plates disposed around the at least one magnetic column. Each of the annular metal plates has an electrical connection end, an annular portion and a heat-dissipating end. The electrical connection end and the heat-dissipation end are located at the two opposite openings of the magnetic core respectively. A thermal-dissipating area of the heat-dissipating end is greater than a cross-sectional area of a connection portion between the heat-dissipating end and the annular portion.

Abstract: A method for generating a license plate defacement classification model, a license plate defacement classification method an electronic device and a storage medium, and related to the technical field of artificial intelligence, and specifically, to the technical field of computer vision and the technical field of intelligent transportation are provided. The method for generating a license plate defacement classification model includes: acquiring training data, wherein the training data includes a plurality of annotated vehicle images, annotated content includes information indicating that a license plate is defaced or is not defaced, and the annotated content further includes location information of a license plate area; and training a first neural network by using the training data, to obtain the license plate defacement classification model for predicting whether the license plate in a target vehicle image is defaced.

Abstract: The present disclosure provides a target detection and model training method and apparatus, a device and a storage medium, and relates to the field of artificial intelligence, and in particular, to computer vision and deep learning technologies, which may be applied to smart city and intelligent transportation scenarios. The target detection method includes: performing feature extraction processing on an image to obtain image features of a plurality of stages of the image; performing position coding processing on the image to obtain a position code of the image; obtaining detection results of the plurality of stages of a target in the image based on the image features of the plurality of stages and the position code; and obtaining a target detection result based on the detection results of the plurality of stages.

Abstract: In various embodiments a computer-implemented method comprises generating, for a current video frame, a set of face motion data indicating whether a set of one or more faces detected in the current video frame has moved since a preceding video frame, generating a set of device motion data associated with one or more movements of an image capture device when capturing the current video frame, and generating a set of global motion data based on the set of face motion data and the set of device motion data, where the set of global motion data identifies a unique face motion when the set of face motion data indicates at least one face in the set of one or more faces has moved, and the set of device motion data indicates less than a threshold amount of motion of the image capture device when capturing the current video frame.

Abstract: A method for configuring a theme color of a terminal device includes obtaining a tone type of a to-be-switched-to picture when it is detected that a terminal device switches a screen picture, determining cool and warm color system information of the picture, identifying arrangement and proportion information of a representative color system of the picture, and configuring a theme color of the terminal device based on the tone type, the cool and warm color system information, and the arrangement and proportion information of the representative color system.

Abstract: The satellite image processing method includes: acquiring a first target satellite image; defogging the first target satellite image through a first neural network to acquire a first satellite image; and adjusting an image quality parameter of the first satellite image through a second neural network to acquire a second satellite image.