In remote sensing applications, segmentation of input satellite images according to semantic information and estimating the category each pixel from a given set tags are great importance for automatic tracking task. It is important in situations such as building detection high resolution images, city planning, environmental preparation, disaster management. Buildings metropolitan areas crowded ...

In this paper, different types of web session similarity metrics are compared and combined for better web session clustering. Syntactic and co-occurrence information are used for similarity calculation. Syntactic information on a web page includes the place of the page in the directory hierarchy. Co-occurrence information is the amount of the occurrences of two web pages in the same sessions. V...

This paper presents an ensemble learning algorithm for liver tumour segmentation from a CT volume in the form of U-Boost and extends the loss functions to improve performance. Five segmentation algorithms trained by the ensemble learning algorithm with different loss functions are compared in terms of error rate and Jaccard Index between the extracted regions and true ones. key words: CT image,...

In this paper we compare the Russian National Corpus to a larger Russian web corpus composed in 2014; the assumption behind our work is that the National corpus, being limited by the texts it contains and their proportions, presents lexical contexts (and thus meanings) which are different from those found ‘in the wild’ or in a language in use. To do such a comparison, we used both corpora as tr...

In association rule mining, interestingness refers to metrics that are applied to select association rules, beyond support and confidence. For example, Merceron & Yacef (2008) recommend that researchers use a combination of lift and cosine to select association rules, after first filtering out rules with low support and confidence. However, the empirical basis for considering these specific met...

In this paper we describe the three approaches we submitted to the Semantic Textual Similarity task of SemEval 2012. The first approach considers to calculate the semantic similarity by using the Jaccard coefficient with term expansion using synonyms. The second approach uses the semantic similarity reported by Mihalcea in (Mihalcea et al., 2006). The third approach employs Random Indexing and ...

This paper presents an unsupervised approach for learning of patterns with spatial and temporal information from a very small number of training samples. The method employs a spiking network with axonal conductance delays that learns the encoding of individual patterns as sets of polychronous neural groups, which emerge as a result of training. A similarity metric between sets, based on a modif...