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637 results about "Quality Score" patented technology

Quality Score is a metric used by Google, Yahoo! (called Quality Index), and Bing that influences ad rank and cost per click (CPC) of ads. To determine the position of the ad on a search engine, each ad is allocated using a process which takes into account the bid and the Quality Score. Ads are then listed in descending order based on the result of that equation. The exact weight of Quality Score versus bid has not been revealed by any of the major search engines, and each company has stated that they reserve the right to continually adjust their ranking methodologies.

Realizing method, device and system for recommending applications

The invention discloses a realizing method, a realizing device and a realizing system for recommending applications. The method includes the following steps: unitization processing the characteristic information of applications, so as to obtain the quality scores of the applications, and determining the correlativity of multiple applications according to the historical behavior data of multiple users; and in case that the information of the application recommended to the user needs to be transmitted to the user, other applications can be wholly or partially recommended to the user according to the quality scores of the other applications and the correlativity between the other applications and the object application, and the object application includes the application used at present or before. According to the realizing method, device and system, the applications can be recommended to the user by referring to the characteristics of the applications, therefore, the newly uploaded or little-user operation applications can be reasonably recommended to the user, the inaccuracy of the subjective judgment in recommending the applications can be overcome, and by combining with the relevance to recommend on the basis, the accuracy in recommending can be further improved, and the user experiencing can be improved.
Owner:BEIJING QIHOO TECH CO LTD

Face image quality evaluation method based on multidirectional evaluation standard and system thereof

The invention provides a face image quality evaluation method based on a multidirectional evaluation standard and a system thereof. The method comprises the steps of acquiring a face image as trainingdata; classifying the training data according to degrading characteristics with different dimensions; performing preliminary evaluation and marking on each kind of images in the classified training data; establishing a branch task which corresponds with each kind of dimension characteristics according to the classification result of the degrading characteristics with different dimensions; establishing a quality evaluation model, performing training, performing multi-branch task predicating on an input to-be-evaluated face image according to the quality evaluation model after training, therebyfinishing face image quality evaluation. According to the method and the system, the image characteristics are extracted by means of a deep neural network, and furthermore comprehensive quality evaluation to multiple image quality affecting factors is finished. An obtained image comprehensive quality score is relatively same with the subjective evaluation of human eyes, and furthermore a relatively high evaluation speed is realized. After the low-quality image is filtered, face identification performance can be effectively improved.
Owner:CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI

Identity identification method and apparatus based on combination of gait and face

The invention relates to an identity identification method and apparatus with the combination of the gait and the face based on deep learning. The apparatus comprises a video acquisition and preprocessing module, a gait feature extraction module, a face feature extraction module and an identification module. The method includes: acquiring a video stream, and performing pedestrian detection and tracking and face detection on the video stream; performing gait feature extraction on human body images, and calculating quality evaluation scores of gait features; performing face feature extraction onface images, calculating quality evaluation scores of face features, and regarding the face image with the highest quality evaluation score as a to-be-identified face image; and performing weightingon the gait features and the face features according to respective quality scores, and inputting the weighted scores into a SVM classifier for identity identification. According to the method and theapparatus, the quality evaluation scores of the gait features and the face features are calculated, weighting is performed according to the quality scores, advantages of face identification and gait identification are combined, the two identification technologies are complemented, the robustness of an identification system is increased, and the accuracy of figure identity identification is improved.
Owner:武汉神目信息技术有限公司

Quality objective evaluation method with no reference images based on multi-scale generative adversarial network

ActiveCN108090902AIntuitively reflect the degree of distortionReflect the degree of distortionImage enhancementImage analysisData setImaging quality
The invention discloses a quality objective evaluation method with no reference images based on multi-scale generative adversarial network. Similar quality images corresponding to distorted images canbe generated through the multi-scale generative adversarial network, and similar quality images in different scales can undergo regression to obtain the image quality scores through convolution nervenetwork. The multi-scale generative adversarial network is trained, and similar quality images are generated for the distorted images through the full-reference image quality evaluation method, and the similar quality images are considered as a real data set for determining network. Three groups of similar quality images in different scales are considered as the data set, and the subjective evaluation score is used as the label, and the image quality score regression network is trained. The distorted image generates a plurality of similar quality images in different scales through the generative network, and generates the image quality score through the image quality score regression network. The invention is advantageous in that the integral distortion degree and the local distortion details are combined, and the quality score of the distorted images can be further determined, and the quality of distorted images can be embodied in a more comprehensive and more accurate manner.
Owner:COMMUNICATION UNIVERSITY OF CHINA
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