The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
AdaBoost algorithm is a kind of very important feature classification machine learning algorithm, But if difficult samples exist in the training samples, With the iterative Number increasing, this easily leads to degeneration Phenomenon, and reduces the generalization ability of the classifier. In view of the face detection under complex background degeneration appeared problem, This article Proposes...
AdaBoost algorithm is a kind of very important feature classification machine learning algorithm, But if difficult samples exist in the training samples, with the iterative Nurnber increasing, this easily leads to degeneration Phenomenon, and reduces the generalization ability of the classifier. In view of the face detection under complex background degeneration appeared problem, This article Proposes...
On the basis of online boosting algorithm, this paper presents an optimized target tracking algorithm. Now, the commonly-used tracking algorithm usually tracks the targets as a whole, thus facing great difficulty in realizing effective tracking while the target is severely shielded. In order to surmount the difficulties resulting from shielding, this paper puts forward block-based target tracking...
In this paper, for every local feature, we propose to learn its similar local features across all positive images, instead of using heuristic distance as similarity measure. Specifically, multiple instance learning (MIL) is employed to simultaneously determine the similar points of a local feature and learn its corresponding discriminative function which can be regarded as some kind of similarity...
AdaBoost was proposed as an efficient algorithm of the ensemble learning field, it selects a set of weak classifiers and combines them into a final strong classifier. However, conventional AdaBoost is a sequential forward search procedure using the greedy selection strategy, redundancy can not be avoided. We proposed a post optimization procedure for the found classifiers and their coefficients based...
In this paper, we accomplish matching score level fusion of multi-biometrics. In order to solve the incomparability among different classifiers' outputs, adaptive confidence transform (ACT) is introduced to convert the raw outputs of different classifiers to the estimates of posteriori probabilities conforming to different users. These posteriori probabilities are then combined using several fusion...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.