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.
Glowworm Swarm Optimization Algorithm (GSO) is one of new swarm intelligence optimization algorithms in recent years. Its main idea comes from the cooperative behavior source among individuals during the process of courtship and foraging. In this paper, in order to improve convergence speed in the late iteration, avoid the algorithm falling into local optimum, and reduce isolated nodes, the Adaptive...
This paper presents a novel approach for improving multi-person tracking using hierarchical group structures. The groups are identified by a bottom-up social group discovery method. The inter- and intra-group structures are modeled as a two-layer graph and tracking is posed as optimization of the integrated structure. The target appearance is modeled using HOG features, and the tracking solution is...
As the international logistics industry develops fast, container loading has become a core part of maritime transport, with its efficiency and safety focused by logistics industry. The enlargement of ships makes the container loading problem much more complex than ever. Traditional ways to study these problems now have been difficult to offer effective solutions, while simulation technology not only...
The Support Vector Machines (SVM) become popular E-Business data mining tools recently, and the datasets of E-Business are usually large-scale. If Support Vector Machines are trained on large-scale datasets, the training time will be very long and the classifier's accuracy will become lower too. As training a large-scale SVM is equated to solve a large-scale quadratic programming (QP) problem, so...
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.