Abstract: The present disclosure relates to a processing method of an abnormal region in an image and an apparatus, and relates to the technical field of image processing. The method includes: generating, for a region to be examined consisting of any one or more pixels in an image to be processed, a plurality of regions to be processed including the region to be examined; respectively calculating respective predicted pixel values of the region to be examined, by using a first machine learning model, according to pixel values in a preset range outside respective regions to be processed; calculating prediction error distributions corresponding to the respective predicted pixel values as a first error distribution, according to original pixel values of the region to be examined; and determining whether the region to be examined belongs to the abnormal region in the image to be processed, according to the first error distribution.

Abstract: Provided are a voice noise reduction method, an electronic device, and a non-transitory computer-readable storage medium. The specific implementation scheme includes determining a to-be-denoised voice spectrum of a to-be-denoised voice signal; performing feature extraction on the to-be-denoised voice spectrum to obtain a local voice spectral feature of the to-be-denoised voice spectrum; determining a global voice spectral feature of the to-be-denoised voice spectrum according to the local voice spectral feature of the to-be-denoised voice spectrum; and determining a masking matrix of an original voice signal in the to-be-denoised voice signal according to the local voice spectral feature and the global voice spectral feature, and determining the original voice signal according to the to-be-denoised voice spectrum and the masking matrix.

Abstract: A system may include at least one computer-readable storage medium including a set of instructions for providing a driver registered in an online platform with a financial program for buying a vehicle, and at least one processor in communication with the computer-readable storage medium, wherein when executing the set of instructions, the at least one processor is directed to: receive data of a plurality of drivers registered in the online platform from an input device, the data including usage history of a plurality of vehicles associated with the plurality of drivers; identify from the plurality of drivers a first group of candidate drivers based on the usage history, each candidate driver is associated with a purchase intention higher than a threshold value; and save a first structured data in the storage medium to identify the first group of candidate drivers.

Abstract: A method of processing input digital image data representing an image into output digital image data, comprising: providing (100) input image data; providing and initializing (200) a level set function representation for approximating the output digital image data; providing (300) a speed function; determining (400) a propagation direction trend map relating to image points of the level set function, said map comprising one or more trend directions associated with said image points so that each one of said image points has an associated trend direction; updating (500, 520) the level set function using the speed function and the propagation direction trend map, so that the speed function is excluded from contributing in the updating of the level set function in image points for which the speed of the speed function is not in the associated trend direction; and providing (700) the output digital image data based on the level set function.

Abstract: A method of processing input digital image data representing an image into output digital image data, comprising: providing (100) input image data; providing and initializing (200) a level set function representation for approximating the output digital image data; providing (300) a speed function; determining (400) a propagation direction trend map relating to image points of the level set function, said map comprising one or more trend directions associated with said image points so that each one of said image points has an associated trend direction; updating (500, 520) the level set function using the speed function and the propagation direction trend map, so that the speed function is excluded from contributing in the updating of the level set function in image points for which the speed of the speed function is not in the associated trend direction; and providing (700) the output digital image data based on the level set function.