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.
Prognosis refers to the prediction of the future health status of a patient. Providing prognostic insight to clinicians is critical for physician decision support. In this paper we present a collaborative disease prognosis strategy leveraging the information of the clinically similar patient cohort, using a Local Spline Regression (LSR) based similarity measure. To improve the reliability of the approach,...
Among ensemble learning methods, stacking with a meta-level classifier is frequently adopted to fuse the output of multiple base-level classifiers and generate a final score. Labeled data is usually split for basetraining and meta-training, so that the meta-level learning is not impacted by over-fitting of base level classifiers on their training data. We propose a novel knowledge-transfer framework...
Recently the improved bag of features (BoF) model with locality-constrained linear coding (LLC) and spatial pyramid matching (SPM) achieved state-of-the-art performance in image classification. However, only adopting SPM to exploit spatial information is not enough for satisfactory performance. In this paper, we use hierarchical temporal memory (HTM) cortical learning algorithms to extend this LLC...
Nearest-Neighbor based Image Classification (N-NIC) has drawn considerable attention in the past several years because it does not require classifier training. Similar to an orderless Bag-of-Feature image representation, the traditional NNIC ignores global geometric correspondence. In this paper, we present a technique to exploit the global geometric correspondence in a nearest neighbor classifier...
The codebooks play a decisive role in the Hough Transform based object detection. We propose a novel approach to generate the codebooks in the manner of parametric regression and integrate inside semantic information drawn from objects and background. Clustering is a popular method for deriving codebooks, but it generally relies on some parameters, which heavily affect the performance of the approaches...
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.