Abstract: A micro inverter, a photovoltaic system and a method for controlling a micro inverter are provided. The micro inverter includes a controller, a primary H-bridge, a transformer, a bi-directional switch arm and a capacitor arm. The controller is configured to: determine a reactive current based on a grid voltage, an equivalent capacitance of an output terminal of the inverter and a grid angle; add the reactive current to a given current to generate an internal phase-shift angle and an external phase-shift angle from a new given current obtained through the addition, where the internal phase-shift angle refers to a phase-shift angle between two arms of the primary H-bridge and the external phase-shift angle refers to a phase-shift angle between the primary H-bridge and the bi-directional switch arm.

Abstract: An electronic apparatus, a control circuit, and a transmission control method includes a control circuit and at least two communication circuits, where the control circuit is configured to obtain first service data, and selectively distribute the first service data to at least one of the communication circuits, and any one of the communication circuits can support one wireless communication protocol.

Abstract: A video classification method and apparatus are provided in embodiments of the present invention. The method includes: establishing a neural network classification model according to a relationship between features of video samples and a semantic relationship of the video samples; obtaining a feature combination of a to-be-classified video file; and classifying the to-be-classified video file by using the neural network classification model and the feature combination of the to-be-classified video file The neural network classification model is established according to the relationship between the features of the video samples and the semantic relationship of the video samples, and the relationship between the features and the semantic relationship are fully considered. Therefore, video classification accuracy are improved.

Abstract: The present invention provides a method and an apparatus for detecting a salient region of an image. Classification processing is obtained by means of pre-training, so as to obtain a classification label, where the classification label is used to indicate a salience detection algorithm for detecting a salient region of the test image. Salience detection is performed on the test image by using the salience detection algorithm indicated by the classification label, so as to obtain the salient region of the test image. Because a salience detection algorithm with the best detection effect is acquired by using the image feature vector of the test image, to detect the salient region of the test image, accuracy of salience detection is improved.

Abstract: The present invention provides a method and an apparatus for detecting a salient region of an image. Classification processing is performed on a test image according to an image feature vector of the test image by using a classifier obtained by means of pre-training, so as to obtain a classification label, where the classification label is used to indicate a salience detection algorithm for detecting a salient region of the test image. Salience detection is performed on the test image by using the salience detection algorithm indicated by the classification label, so as to obtain the salient region of the test image. Because a salience detection algorithm with the best detection effect is acquired by using the image feature vector of the test image, to detect the salient region of the test image, accuracy of salience detection is improved.