Abstract: An electronic device and method for audio recommendation and generation are disclosed. The electronic device receives textual information that indicates a plurality of scenes for video content, and determines a first plurality of features for the plurality of scenes. The electronic device determines a set of positions in the textual information based on the determined first plurality of features. A set of audio files are to be inserted at the set of positions related to a set of scenes of the plurality of scenes. The electronic device determines, by an artificial intelligent (AI) engine, the set of audio files for the set of scenes, based on a second plurality of features and the first plurality of features related to the set of scenes. The electronic device controls a display device to display first information corresponding to the set of positions and second information corresponding to the set of audio files.

Abstract: An electronic apparatus and method for heatmap visualization of object detections is provided. The electronic apparatus inputs an image frame including an object of interest to Deep Neural Network (DNN) model and extracts an object detection result associated with the object of interest as output of the DNN model for the input image frame. The object detection result includes bounding box coordinates for the object of interest. The electronic apparatus segments the input image frame into a plurality of image portions based on the bounding box coordinates and determines, for each of the plurality of image portions, a weight value indicative of a likelihood that a corresponding image portion belongs to the object of interest. The electronic apparatus generates, based on the determined weight value, a visualization frame which includes heatmap visualization of a region that is included in the image frame and is bounded by the bounding box coordinates.

Abstract: An electronic device includes a memory to store neural network model trained for classification tasks of real-time applications. The neural network model is trained with plurality of training data points. The electronic device includes circuitry to retrieve a plurality of external data points. The electronic device applies the neural network model on the plurality of external data points to determine a plurality of impact scores for each external data point. The plurality of impact scores indicates amount of contribution of each training data point towards a prediction of each external data point. The electronic device selects a set of external data points based on the plurality of impact scores. The electronic device updates the plurality of training data points with the set of external data points to generate a second plurality of training data points and re-trains the neural network model based on the second plurality of training data points.

Abstract: An electronic apparatus and method for heatmap visualization of object detections is provided. The electronic apparatus inputs an image frame including an object of interest to Deep Neural Network (DNN) model and extracts an object detection result associated with the object of interest as output of the DNN model for the input image frame. The object detection result includes bounding box coordinates for the object of interest. The electronic apparatus segments the input image frame into a plurality of image portions based on the bounding box coordinates and determines, for each of the plurality of image portions, a weight value indicative of a likelihood that a corresponding image portion belongs to the object of interest. The electronic apparatus generates, based on the determined weight value, a visualization frame which includes heatmap visualization of a region that is included in the image frame and is bounded by the bounding box coordinates.