Abstract: A weak password detection method and device based on deep learning, an electronic device, and a storage medium are provided. The method includes: acquiring a password character string to be detected; processing, by applying a fully trained weak password detection model, the password character string to be detected to obtain a strong/weak password classification label of the password character string to be detected, the fully trained weak password detection model being obtained by training a deep learning model with a password character string as an input and a strong/weak password classification label corresponding to the password character string as a supervision; and marking the password character string to be detected as a weak password under the condition that the strong/weak password classification label is a weak password label.

Abstract: A method and apparatus of processing and displaying images captured using an in vivo capsule camera are disclosed. One or more overlapped areas between a target image and each image in a neighboring image group are determined, which comprises at least two neighboring images around the target image. Marked pixels in the target image are then determined, where a pixel in the target image is designated as a marked pixel if the pixel is within an overlapped area between the target image and at least one neighboring image. If the total number of the marked pixels in the target image exceeds a threshold and the number of the marked pixels associated with the overlapped area(s) between the target image and any image in the neighboring image group is below the threshold, the target image is excluded from a set of images to be displayed on a display device.

Abstract: A method and apparatus of processing and displaying images captured using an in vivo capsule camera are disclosed. One or more overlapped areas between a target image and each image in a neighboring image group are determined, which comprises at least two neighboring images around the target image. Marked pixels in the target image are then determined, where a pixel in the target image is designated as a marked pixel if the pixel is within an overlapped area between the target image and at least one neighboring image. If the total number of the marked pixels in the target image exceeds a threshold and the number of the marked pixels associated with the overlapped area(s) between the target image and any image in the neighboring image group is below the threshold, the target image is excluded from a set of images to be displayed on a display device.