Abstract: A moving-coil geophone zero-phase corrector based on a state variable shaper is provided. The zero-phase corrector includes a state variable shaper module, a differential-to-single-ended module, and a single-ended-to-differential module. After a moving-coil geophone signal is input as a differential signal, the differential-to-single-ended module converts the signal into a single-ended signal suitable for filtering, the high-pass filter, band-pass filter, and low-pass filter in the state variable shaper module correct the phase characteristic of the geophone's frequency response to a zero-phase attribute, and finally, the single-ended-to-differential module converts the single-ended signal back into a differential signal for output.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for image processing include obtaining an input image and a modification input, wherein the input image depicts an object and the modification input indicates a change to the object. A feature map is generated, and the feature map represents the object based on the input image. The feature map is transformed to obtain a transformed feature map based on the modification input. The transformed feature map represents the change to the object. A synthetic image is generated, using an image generation model, based on the input image and the transformed feature map. The synthetic image depicts the change to the object.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for image generation include obtaining a concept input, a source image, and an input mask, where the concept input represents a concept, the source image depicts a scene, and the input mask indicates a location for the concept in the scene. Concept features are generated by performing a style transfer from the source image to the concept input based on the input mask. A synthetic image is generated, using an image generation model, based on the concept features. The synthetic image depicts the concept from the concept input within the scene from the source image at the location indicated by the input mask.

Abstract: The present disclosure relates to a connector for a motor, a motor, and a vehicular compressor. The connector has a substrate and a plurality of stator terminals disposed on the substrate. The connector is further disposed with an insulation adhesive receiving part having a body detachably secured on the substrate; an opening for at least two stator terminals of the plurality of stator terminals to pass through; and a panel extending outwardly from a side of the body away from the substrate and circumferentially disposed along the opening for enclosing a space to receive the insulation adhesive. A first sealing portion is disposed on a side of the body proximate to the substrate, and a second sealing portion is disposed at a corresponding location of the substrate. The first sealing portion and the second sealing portion are sealed, press-fit and circumferentially disposed along the opening.

Abstract: A system for loading dynamic stress on subgrade or foundation based on multi-servo channel and a control method thereof. The system comprises: connecting plate; five dynamic actuators are hinged between connecting frame and the connecting plate; four of them form 4-RPR parallel mechanism, another one is arranged in middle of the 4-RPR parallel mechanism; loading part is mounted at center under the connecting frame; and restraining plate is arranged under the loading part and freely contacts with the loading part; four static actuators are arranged between the restraining plate and the connecting plate; wherein, the static actuators and dynamic actuators are dynamic-static cooperative controlled through multi-servo channel, to simulate principal stress axes rotation effect of a soil body of subgrade or foundation The system can realize the principal stress axes rotation effect in the subgrade or foundation through dynamic-static cooperative loading and can simulate different traffic load forms.

Abstract: A non-differential sensing circuit for semiconductor Non-Volatile Memories (NVMs) is disclosed. The circuit comprises a half latch, a switch device, a reset device, a PMOSFET device and an NMOSFET device. The half latch has a voltage signal input node and a digital voltage signal output node. The PMOSFET device has a source connected to a digital voltage rail and a drain connected to the voltage signal input node. The NMOSFET device has a drain connected to the gate of the PMOSFET device, a gate applied with a bias voltage and a source connected to a bitline read path. The circuit is tuned to threshold voltages of the PMOSFET device and the NMOSFET device for sensing the threshold voltage of a NVM cell. By sensing threshold voltage states of the NVM cell, a bit information stored in the NVM cell can be fast determined.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for training a mask refinement neural network via simulated mask generation and point-sampling. The disclosed system generates simulated masks for objects in a plurality of digital images by modifying masked regions in a plurality of ground-truth masks for the objects utilizing one or more mask modification operations. The disclosed system also generates, utilizing a mask refinement neural network, a plurality of estimated refined masks for the objects in the plurality of digital images based on the plurality of digital images and the simulated masks. The disclosed system further adjusts parameters of the mask refinement neural network by utilizing a matting loss based on a plurality of separate point-sampling operations to reduce differences between the plurality of estimated refined masks and the plurality of ground-truth masks.

Abstract: Methods and systems for content-based media attribute assessment. A media item including a set of video frames each including initial content associated with a content type is identified. A spatial transformation operation with respect to the set of video frames to obtain a set of spatially transformed video frames is performed. One or more video frames of the set of spatially transformed video frames including transformed content that satisfies one or more quality criteria are identified. A set of model weights associated with the transformed content of the identified one or more video frames is determined. A model pipeline associated with a content sharing platform is modified to include the set of model weights for application to outputs of one or more artificial intelligence (AI) models trained to predict quality metrics associated with media items including content having the content type.

Abstract: Methods and systems for improving accuracy and reliability of artificial intelligence (AI)-predicted attributes for media items are provided. A first and second variant of a media item are obtained, and their respective first and second quality metrics are identified using an AI model. Based on these quality metrics, a first quality loss value, representing a deviation of one or both metrics from a reference quality metric, and a second quality loss value, representing a difference between the first and second quality metrics, are determined. These loss values are then provided for retraining the AI model to predict improved quality metrics for additional media items.

Abstract: A motor stator, a motor, and a vehicular compressor. The motor stator includes a stator core; a first insulated end plate and a second insulated end plate mounted at opposite end surfaces of the stator core; a wire wrapping around the stator core and the first and second insulated end plates, the wire having a conducting core and an insulated outer sheath; and a wiring board mounted to an axial outer side of the first insulated end plate. The first insulated end plate includes a plurality of insulated treatment positions and the wiring board includes a plurality of casing portions through which the insulated treatment positions can be accessed for providing insulation material.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for image processing include obtaining an input image and a modification prompt, where the input image depicts an object with a first attribute and the modification prompt describes a modification from the first attribute to a second attribute different from the first attribute, encoding the modification prompt to obtain a text embedding, where the text embedding represents the modification in an embedding space, and generating a modified image based on the input image and the text embedding, where the modified image depicts the object with the second attribute.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for image processing include obtaining an input image and a reference effect prompt, where the reference effect prompt indicates an image effect for the input image, generating an intermediate image based on the reference effect prompt, where the intermediate image depicts the image effect applied to the input image, and generating a synthetic image based on the input image, the reference effect prompt, and the intermediate image, where the synthetic image depicts the image effect applied to the input image and has a higher resolution than the intermediate image.

Abstract: Disclosed are a multimodal weakly-supervised three-dimensional (3D) object detection method and system, and a device. The method includes: shooting multiple two-dimensional (2D) red, green and blue (RGB) images with a camera, acquiring ground points by a vehicle LiDAR sensor and generating a 3D frustum based on 2D box labels on each of the 2D RGB images; filtering ground points in the 3D frustum and selecting a region with most 3D points; generating a 3D pseudo-labeling bounding box of an object according to the region with the most 3D points; training a multimodal superpixel dual-branch network with the 3D pseudo-labeling bounding boxes as labels and the 2D RGB image and the 3D point cloud as inputs; and inputting a 2D RGB image of a current frame and a 3D point cloud of a current scenario to a trained multimodal superpixel dual-branch network to generate an overall 3D point cloud.

Abstract: A system for loading dynamic stress on subgrade or foundation based on multi-servo channel and a control method thereof. The system comprises: connecting plate; five dynamic actuators are hinged between connecting frame and the connecting plate; four of them form 4-RPR parallel mechanism, another one is arranged in middle of the 4-RPR parallel mechanism; loading part is mounted at center under the connecting frame; and restraining plate is arranged under the loading part and freely contacts with the loading part; four static actuators are arranged between the restraining plate and the connecting plate; wherein, the static actuators and dynamic actuators are dynamic-static cooperative controlled through multi-servo channel, to simulate principal stress axes rotation effect of a soil body of subgrade or foundation The system can realize the principal stress axes rotation effect in the subgrade or foundation through dynamic-static cooperative loading and can simulate different traffic load forms.

Abstract: A computer system and a computer-implement method include obtaining a source image and a modification input that indicates a target edit to the source image and generating a modification encoding representing the target edit. An image generation model generates an output image that depicts the source image with the target edit based on the source image and the modification encoding. The image generation model is trained to perform a pose modification task and a part replacement task.

Abstract: Systems and methods for instance segmentation are described. Embodiments include identifying an input image comprising an object that includes a visible region and an occluded region that is concealed in the input image. A mask network generates an instance mask for the input image that indicates the visible region of the object. A diffusion model then generates a segmentation mask for the input image based on the instance mask. The segmentation mask indicates a completed region of the object that includes the visible region and the occluded region.

Abstract: A system and methods are disclosed for optimal format selection for video players based on visual quality. The method includes determining, based on sampled frames of a video, a plurality of quality scores for the video, wherein each quality score is associated with a corresponding parameter combination that includes a corresponding video format, a corresponding transcoding configuration, and a corresponding display resolution. The method further includes identifying, among the plurality of quality scores, a first quality score that is associated with a first parameter combination, which includes a first display resolution matching a display resolution of a client device, and causing a first video format to be selected for the client device using the first parameter combination that includes the first display resolution matching the display resolution of the client device.

Abstract: A method for generating, for a video stream of a first spatial resolution and a first temporal resolution, a first reduced quality steam of a second spatial resolution and a second reduced-quality stream of a second temporal resolution. A first subset of STPs is sampled from the first reduced-quality stream and a second subset of STPs is sampled from the second reduced-quality stream. Using a machine learning model (MLM) the STPs are processed to identify a quality score for each quality-representative STPs that are representative of a quality of the video stream. One or more quality-improving actions for the video stream are identified using the quality scores of the quality-representative STPs.

Abstract: Obtaining a robustly trained image quality assessment machine learning model by training a machine learning model using a target image obtained by upscaling a downscaled reference image, an adversarial image obtained by upscaling a result of distorting the downscaled image, obtaining, from the machine learning model with first parameter values, a first result value for the target image relative to the reference image and a second result value for the adversarial image relative to the reference image, including, in the machine learning model, a result of subtracting a scaled gradient from the first parameter values, wherein the scaled gradient is a result of a product of a gradient of a loss function that is a maximum among zero and a result of adding a defined hinge loss value to difference between the result values.

Abstract: Systems and methods for image segmentation are described. Embodiments of the present disclosure receive an image depicting an object; generate image features for the image by performing a convolutional self-attention operation that outputs a plurality of attention-weighted values for a convolutional kernel applied at a position of a sliding window on the image; and generate label data that identifies the object based on the image features.