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.
The problem of malicious contents in blogs has reached epic proportions and various efforts are underway to fight it. Blog classification using machine learning techniques is a key method towards doing it. We have devised a machine learning algorithm where features are created from individual sentences in the body of a blog by taking one word at a time. Weights are assigned to the features based on...
This paper proposes a method for the identification of individuals from their gait using fuzzy logic. Gait signature is first extracted in the form of a spatiotemporal representation called Gait Energy Image (GEI). Since the dimension of GEI is very high, we use fuzzy principal component analysis (FPCA) for dimension reduction. Unlike traditional PCA, it helps to get rid of the problems of outliers...
This paper presents a new learning algorithm for multitask pattern recognition (MTPR) problems. We consider learning multiple multiclass classification tasks online where no information is ever provided about the task category of a training example. The algorithm thus needs an automated task recognition capability to properly learn the different classification tasks. The learning mode is ldquoonlinerdquo...
This paper presents a learning model of multitask pattern recognition (MTPR) which is constructed by several neural classifiers, long-term memories, and the detector of task changes. In the MTPR problem, several multi-class classification tasks are sequentially given to the learning model without notifying their task categories. This implies that the learning model is supposed to detect task changes...
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.