Abstract: A display device and an operation method of the display device are provided in the present disclosure. The display device includes a display screen a sound-generation driving module, and further includes an acoustic scanning module, arranged on a non-display side of the display screen and configured to determine a spatial contour of a space where the display device is located through acoustic scanning; a viewer position detection module, configured to detect viewer coordinates in the space where the display device is located; and a control module, configured to control the sound-generation driving module to generate sound in accordance with the spatial contour and the viewer coordinates.

Abstract: The present disclosure provides a self-learning collaborative control method for active steering and yaw moment for a motor vehicle, including a first step of constructing fundamental formulas which are stored in a vehicle ECU, and a second step of calculating an active steering angle ?C and a yaw moment Mc on line by the vehicle ECU according to following sub-steps during a driving process of the motor vehicle, and controlling a driving state of the motor vehicle according to ?C and Mc. The second step includes a first sub-step of collecting raw real-time parameter values, a second sub-step of performing calculation by the identifier and the control target reference model, a third sub-step of calculating ?C and Mc. The present disclosure can realize the self-learning collaborative control of active steering and yaw moment without requiring a system control model and correct a driver's steering operation.

Abstract: The present application discloses a method, device, and system for processing a medical image. The method includes obtaining, by one or more processors, a target image, segmenting, by the one or more processors, a target region image from the target image, wherein the target region image comprises a target object region in the target image, analyzing, by the one or more processors, the target region image based at least in part on a machine learning model, and obtaining by the one or more processors, a recognition result based at least in part on the analysis of the target region image.

Abstract: A method for preparing biochar and hydrogen by utilizing anaerobic fermentation byproducts, the method including: (1) mixing a first straw, seeding sludge and distilled water, and then carrying out anaerobic fermentation to obtain a mixed product after fermentation; (2) performing separation on the mixed product to obtain a second straw and biogas slurry; and (3) carbonizing the second straw to obtain biochar, and collecting gas after a pressurized catalytic reaction on the biogas slurry to obtain hydrogen.

Abstract: An image recognition method includes: obtaining an image; extracting a target image region corresponding to a target part from the image, wherein the target image region includes a target object; determining a location of the target object in the target image region (i) according to pixel values of pixels in the target image region and a location relationship between the pixels, or (ii) inputting the target image region to a trained segmentation model to obtain the location of the target object in the target image region; and displaying a recognition result of the image, wherein the recognition result indicates the location of the target object in the target image region.

Abstract: An image recognition method includes: obtaining an image; extracting a target image region corresponding to a target part from the image, wherein the target image region includes a target object; determining a location of the target object in the target image region (i) according to pixel values of pixels in the target image region and a location relationship between the pixels, or (ii) inputting the target image region to a trained segmentation model to obtain the location of the target object in the target image region; and displaying a recognition result of the image, wherein the recognition result indicates the location of the target object in the target image region.

Abstract: The present application discloses a method, device, and system for processing a medical image. The method includes obtaining, by one or more processors, a first medical image, wherein the first medical image includes a representation of a target organ, and processing, by the one or more processors, the first medical image based at least in part on a first machine learning model. A classification result associated with the first medical image and a first image of a target region in the first medical image are obtained based at least in part on the processing of the first medical image using the first machine learning model.

Abstract: The present application discloses a method, device, and system for processing a medical image. The method includes obtaining, by one or more processors, a target image, segmenting, by the one or more processors, a target region image from the target image, wherein the target region image comprises a target object region in the target image, analyzing, by the one or more processors, the target region image based at least in part on a machine learning model, and obtaining by the one or more processors, a recognition result based at least in part on the analysis of the target region image.