Intelligent photographing method based on user preference multi-dimensional driving
A multi-dimensional, user-friendly technology, applied in the direction of kernel methods, neural learning methods, color TV parts, etc., to achieve strong generalization ability, increase interest and satisfaction, and effective scoring
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[0022] Such as figure 1 As shown, a multi-dimensionally driven intelligent camera method based on user preference includes the following specific steps:
[0023] Step 1, the initial positioning of the photo scene, using the pre-trained lightweight network to identify the category of the photo scene, specifically:
[0024] S101, cache the preview image in the camera and denote it as I q , using the trained convolutional neural network for outdoor scene recognition (shooting scenes are divided into K categories);
[0025] S102, the scene category is matched with the scene category that exists in the pre-trained network, if the preview image is in the kth category scene, i.e. q ∈k (k=1,2,...K), then go to step 2; otherwise, shoot directly without performing subsequent steps.
[0026] Step 2, extract the feature vectors of the preview image and the professional portrait photos in the scene, and match them according to the similarity, and select the most similar pictures, specif...
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