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.
We present a very general algorithm for structured prediction learning that is able to efficiently handle discrete MRFs/CRFs (including both pairwise and higher-order models) so long as they can admit a decomposition into tractable subproblems. At its core, it relies on a dual decomposition principle that has been recently employed in the task of MRF optimization. By properly combining such an approach...
This paper proposes a novel pose-invariant segmentation approach for left ventricle in 3D CT images. The proposed formulation is modular with respect to the image support (i.e. landmarks, edges and regional statistics). The prior is represented as a third-order Markov Random Field (MRF) where triplets of points result to a low-rank statistical prior while inheriting invariance to global transformations...
Rooting process of wheat was modeled in use of Linden Mayer system in the present study. Rooting rules along with growth cycle were concluded based on topology and biology analysis, in which the seminal roots and crown roots were treated separately. Meanwhile, some easy-to-use key parameters which are agronomical meaningful were proposed, including time, size, orientation and so on. After these preparations,...
In the paper, we present a novel approach to modeling plants from images by detecting apex features. First, an effective algorithm is proposed to extract apex features in volumetric data recovered from the images. It provides position and pose information for assigning 3D generic leaves. Then, the 3D leaf shapes are determined by an optimization based on the volume. Finally, Branches are modeled by...
We present an approach to decomposing branching volume data into sub-branches. First, a metric is proposed for evaluating local convexities in volumetric data, and it is a criterion for global selection of tip points. Second, a multi-path growing strategy is adopted to segment the volumes based on a DFS transformation starting from the tips. Experiments show that this approach is capable of generating...
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.