Classification of remote sensing image and range data is normally done in 2D space, because anyhow most sensors capture the surface of the earth from a close-to vertical direction and thus vertical structures, e.g. at building façades are not visible ...

For scenery character detection, we introduce environmental context, which is modeled by scene components, such as sky and building. Environmental context is expected to regulate the probability of character existence at a specific region in a scenery ...

The efficient reuse of requirements is a main challenge in industries that offer products with a high degree of reuse in their components, like the automotive industry. Here, an efficient and effective variability management (VM) that is highly ...

Shape-descriptor (e.g. Adjacent Contour Segments, i.e. kAS) and key point-descriptor (e.g. Scale Invariant Feature Transform, i.e. SIFT) are widely used for computer vision. However, few works principally integrate shape-descriptor and key point-...

This paper addresses the issue of the weak association between brain MRI intensity value and anatomical meaning of MR image pixels. By investigating the deformation on brain lateral ventricles and compression from tumor, the correlation between them is ...

Optical character recognition (OCR) is a popular research topic in artificial intelligent area. One of the most important parts of OCR is word recognition. So in this paper, we propose a combination method of selected subsets of Zernike features and MLP ...

This paper presented a machine vision system with a color linear CCD to identify several China wheat classes. However, these images were deformed due to color linear CCD itself, image noise and uneven brightness also existed. The image needs to be ...

Error model customization for different work type of complex CNC equipments is significant to identify and compensate the errors of CNC integrated manufacturing, and further to achieve process optimization and product quality control. Traditional error ...

The objective of this paper is to evaluate the classification performance of several feature extraction and classification methods for exotic wood texture images as dataset. The Gray Level Co-occurrence Matrix, Local Binary Patterns, Wavelet, Ranklet, ...

This paper proposes a new approach to data selection, a key issue in classification problems. This approach, which is based on a feature selection algorithm and one instance selection algorithm, reduces the original dataset in two dimensions, selecting ...

Support Vector Machines, a new generation learning system based on recent advances in statistical learning theory deliver state-of-the-art performance in real-world applications such as text categorization, hand-written character recognition, image ...

In this paper we present a new feature modeling technique. This work was motivated by the fact that although for over two decades feature modeling techniques are used in software research for domain analysis and modeling of Software Product Lines, it ...

Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of high dimensionality, e.g. 128-dimension in the case of SIFT. This limits ...

Large web search engines have to answer thousands of queries per second with interactive response times under tight latency constraints. Query processing is a major cost factor in operating large web search engines. To keep up with this immense workload,...

Result caching is an efficient technique for reducing the query processing load, hence it is commonly used in search engines. In this paper, we study query result caching and proposes a cache management policy for achieving higher hit ratios compared to ...

General Game Playing (GGP) research aims at designing intelligent game playing agents that, given the rules of any game, automatically learn strategies to play and win without human intervention. Our GGP agent can play the wide variety of heterogeneous ...

We proposed [1] a feature binding method to generate a MPEG-7 compliant feature vector, defined as C-MP7. Here, we study the excellence of C-MP7 as a feature vector, using either low- or high-dimensional chaos. With high-dimensional chaos-based C-MP7, ...

Most text categorization methods are based on the vector-space model which ignores the structural information, such as the order and co- occurrence of words within the text. In this paper we describe a novel approach of text classification using graph ...

The paper breaks the routine and makes a new exploration in office rental pricing. Merging the Hedonic model and the characteristics pricing, building effective multi-linear function of the form of office Hedonic models, abstracting the most important ...

Today, the software environment paradigm is shifting to service-oriented computing, based on key features that reflect business concerns. The SOMA and SOUP methodologies can be used to develop service-oriented applications. However, these approaches ...