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The embodiment of the invention provides a tomato maturity prediction method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring a color image, one-dimensional near infrared spectrum data and one-dimensional ultrasonic spectrum data of a tomato; performing feature extraction on the color image to obtain a visual feature vector; converting the one-dimensional near infrared spectrum data into two-dimensional near infrared spectrum data, and performing feature extraction on the two-dimensional near infrared spectrum data to obtain a near infrared spectrum feature vector; performing feature extraction on the one-dimensional ultrasonic spectrum data to obtain an ultrasonic feature vector; based on an attention mechanism, performing feature fusion on the visual feature vector, the near infrared spectrum feature vector and the ultrasonic feature vector to obtain a target fusion feature vector; and predicting the target fusion feature vector to obtain the maturity. According to the invention, the accuracy of tomato maturity prediction is improved.

The application discloses a kind of molecular modeling method and modeling system based on electron density, wherein the method comprises: obtaining atomic coordinate information in target molecule;Based on atomic coordinate information, electron density grid point information of target molecule is obtained at preset resolution;From electron density grid point information, target electron density value greater than preset electron density value is extracted, and 3-dimensional matrix formed by target electron density value is constructed as the molecular model of target molecule.The technical scheme provided by the application solves the problem that the features contained in the traditional molecular representation model are insufficient.

This application is applicable to the field of terminal technologies, and in particular, to an artificial intelligence (Artificial Intelligence, AI) terminal-based screenshot display method and apparatus, and a terminal device. The screenshot display method is applied to a terminal device having a foldable screen. The foldable screen includes a first display and a second display. The screenshot display method includes: obtaining a first included angle between the first display and the second display; performing a screen capturing operation on current display content of each of the first display and the second display, to obtain a first screenshot corresponding to the first display and a second screenshot corresponding to the second display; and displaying the first screenshot and the second screenshot based on the first included angle. The first included angle between the first display and the second display is obtained during screen capturing, so that three-dimensional display of the first screenshot and the second screenshot can be performed based on the first included angle, to fully reflect foldable and bendable characteristics of the terminal device having a foldable screen, and improve a display effect of the screenshots.