Abstract: This application relates to a cover assembly of a secondary battery. The cover assembly includes a cover plate with an air hole; a blocker inserted into and blocking the air hole; a sealing member disposed between the blocker and the cover plate configured to seal a gap between the blocker and the cover plate; and a fastener disposed inside the air hole. The fastener is connected to the cover plate, the blocker is connected to the cover plate through the fastener. The fastener is configured to deform in response to a temperature rise, so that the blocker stops blocking the air hole. The blocker stops blocking the air hole as a temperature inside a housing rises, to discharge gas from the housing through the air hole. In this way, the secondary battery can be prevented from an explosion, while partial heat is taken away through gas discharge.

Abstract: A neural network training method includes: determining first coordinates of a pupil reference point in a first image in a first camera coordinate system, and determining second coordinates of a cornea reference point in the first image in the first camera coordinate system, wherein the first image comprises at least an eye image; determining a first line-of-sight direction of the first image according to the first coordinates and the second coordinates; performing line-of-sight detection on the first image through the neural network to obtain a first detected line-of-sight direction; and training the neural network according to the first line-of-sight direction and the first detected line-of-sight direction.

Abstract: A neural network training method and apparatus, a gaze tracking method and apparatus, and an electronic device are provided. The neural network training method includes: determining a first gazing direction according to a first camera and a pupil in a first image, wherein the first camera is a camera for photographing the first image, and the first image at least includes an eye image; detecting, by means of a neural network, a gazing direction of the first image to obtain a first detected gazing direction; and training the neural network according to the first gazing direction and the first detected gazing direction.

Abstract: Disclosed in the present disclosure are a driver attention monitoring method and apparatus and an electronic device. The method includes: capturing, by a camera arranged on a vehicle, a video of a driving area of the vehicle; determining, according to each of multiple frames of face images of a driver in the driving area included in the video, a type of a gazing area of the driver in the frame of face image, where the gazing area of each frame of face image is one of multiple types of defined gazing areas obtained by dividing a space area of the vehicle in advance; and determining an attention monitoring result of the driver according to a type distribution of gazing areas of the frames of face images included within at least one sliding time window in the video.