4 results about "Eigenface" patented technology

The invention discloses a medical image data management method and system based on artificial intelligence, and relates to the technical field of data management, and the method comprises the steps: collecting medical image data, converting the medical image data into an initial five-dimensional tensor, carrying out the preprocessing through a pulse neural network, and outputting a spatial-temporal characteristic spectrum; performing spatio-temporal joint feature face analysis on the spatio-temporal feature map by adopting an incremental feature space updating algorithm, extracting cross-slice features in combination with a three-dimensional convolution kernel, and generating a dimensionality reduction feature vector sequence; inputting the desensitization feature vector into a parallel detection network to generate a credibility scoring report; and triggering federal learning according to the credibility scoring report, dynamically updating the feature space parameters, and synchronizing the feature space parameters to the edge node through a secure communication protocol. Through high-dimensional tensor pulse coding and spatio-temporal joint feature analysis, the calculation efficiency and feature representation precision of the multi-modal medical image are improved.

The application relates to the field of IT applications and provides a face image generation method and device with face attributes and application thereof. The method comprises the following steps: obtaining a target face attribute image and a face image to be edited; inputting the target face attribute image and the face image to be edited into a face image generation network to obtain a target face image generated by the face image generation network; the face image generation network is used for generating the target face image based on the target face attribute image and the face image to be edited; wherein the face image generation network is trained based on a face sample image set, a feature face sample image set and a sample face attribute image extracted from the feature face sample image set. The method provided in the application can solve the technical problem that the appearance form of the face attribute on the generated face image is uncontrollable, and the generation efficiency of the face image with the face attribute is improved.

Embodiments of the present application relate to the technical field of computer vision, and provide a face image processing method and device and a storage medium, the method comprising: obtaining candidate face feature coefficients of a first user; obtaining a candidate face shape and a candidate face texture according to the candidate face feature coefficients, a preset eigenface, an average face shape and an average face texture vector; generating a candidate adversarial patch based on the candidate face shape and the candidate face texture; obtaining a candidate adversarial sample, the candidate adversarial sample being obtained by superimposing the candidate adversarial patch and an attacker face image of a second user; obtaining a similarity between the candidate adversarial sample and a target face image; if the similarity is less than a preset value, updating the candidate feature coefficients and the candidate adversarial patch until the similarity is greater than the preset value, and outputting the candidate adversarial patch at this time as a target adversarial patch. The present scheme can improve the adversarial property of the adversarial patch and avoid reducing the attack effect due to deformation or face fitting degree.

The present application relates to face recognition technology, in particular to a face database building and updating method and device based on mobile terminal and a storage medium, the method comprising: uploading dynamic video and face photos of the face through the mobile terminal; extracting three-dimensional geometric features of the face through the dynamic video, generating corresponding three-dimensional feature faces according to the three-dimensional geometric features and the reference photos, and storing the three-dimensional feature faces into the face database; simulating the three-dimensional feature faces according to the light intensity, angle, shielding state, skin color and age information of the reference photos, comparing the similarity of the reference photos and the simulated three-dimensional feature faces; and replacing the three-dimensional feature faces stored in the face database through the judgment of the first similarity threshold and the second similarity threshold. The present application reduces the difficulty of collecting the face database and improves the accuracy and comprehensiveness of face recognition.