In this paper, we propose a new L1-Norm-Based two-dimensional locality preserving projections (2DLPP-L1). Traditional 2D-LPP can preserve local structure and extract feature directly form matrices, which shows great a...
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In this paper, we propose a new L1-Norm-Based two-dimensional locality preserving projections (2DLPP-L1). Traditional 2D-LPP can preserve local structure and extract feature directly form matrices, which shows great advantages. However, it is based on L2 norm. It is well known that L2-norm-based criterion is sensitive to outliers. We generalize 2D-LPP to its corresponding L1-norm-based version, i.e. 2DLPP-L1, which is more robust against outliers. To evaluate the performance of 2DLPP-L1, several experiments are performed on the ORL face databases. Experimental results demonstrate that 2DLPP-L1 has better performance than its related methods.
Content-based image retrieval has become an important research area. In order to extract the semantic information within the user’s query concept, we propose an image retrieval method based on regional objects. It is...
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Content-based image retrieval has become an important research area. In order to extract the semantic information within the user’s query concept, we propose an image retrieval method based on regional objects. It is regarded as the pre-processing of a given query image, that is to say, when we get a query image, it needs us to segment the regional object which is useful or interesting, and retrieve according to the segmented fragment. Moreover, we propose a correlation coefficient based color representation. Experimental results demonstrate that our proposed approach performs much better than its related methods. Furthermore, the presented system has a high retrieval precision and keeps color consistency between the similarity images.
This paper presents the architecture that supports the collaborative model ACEM (Advanced Collaborative Educational Model) to assist educators in the collaborative design of learning activities, supported by a high-le...
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This paper presents the architecture that supports the collaborative model ACEM (Advanced Collaborative Educational Model) to assist educators in the collaborative design of learning activities, supported by a high-level graphical tool. ACEM embraces the research areas of computer Supported Cooperative Work (CSCW) and learning Design (LD). Some facilities are considered in order to implement the online interactions between educators, namely a shared whiteboard and a conversation room. A workflow descriptive model of the educators' teamwork is also introduced.
This paper presents the Advanced Collaborative Educational Model (ACEM) for conception of collaborative learning activities. It is based on collaboration between teachers through virtual interactions, reutilization, i...
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This paper presents the Advanced Collaborative Educational Model (ACEM) for conception of collaborative learning activities. It is based on collaboration between teachers through virtual interactions, reutilization, interoperability and adaptability of learning activities. The definition of learning activity is oriented to a constructivist approach. Tagging collaboration and ontologies are also considered in order to facilitate sharing knowledge in a more effective and personalized way. The main goal of this research is to describe teachers' procedures when interacting with the collaborative environment and to develop mechanisms to support teachers in their tasks, mainly in the creation of learning activities to be used in an e-learning context. The model will be implemented through a high-level graphical tool that facilitates synchronous and asynchronous communication.
We present Open Review, a web-based platform aimed at stimulating executable papers by means of post-publication peer-review. Its goal is to bring computerscience researchers to collaboratively build their work upon ...
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We present Open Review, a web-based platform aimed at stimulating executable papers by means of post-publication peer-review. Its goal is to bring computerscience researchers to collaboratively build their work upon previous research results, in such a way that transparency, reproducibility and sustainability of research results are greatly improved. The main design goals of the platform are clarity, conciseness, and reproducibility. Its main features are to: (i) provide incentives for making research communities to participate, (ii) make papers executable by means of boards’ annotations, without necessarily involving the authors of an article, and (iii) give snapshots of the current research state on any given article.
The Association for the Advancement of artificialintelligence, in cooperation with Stanford University's Department of computerscience, presented the 2010 Spring Symposium Series Monday through Wednesday, March ...
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A mass of high-quality information included in Deep Web can be accessed, which is still growing rapidly with the rapid development of the World Wide Web. Therefore it becomes more and more important to find the Web da...
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Active learning is a hot topic in machinelearning field. The main task of active learning is to automatically select the representative instances for efficiently reducing the sample complexity. This paper presents a ...
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When the training dataset is very large, the learning process of potential support vector machine takes up so large memory that the training speed is very slow. To accelerate the training speed of the potential suppor...
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The support vectors play an important role in the training to find the optimal hyper-plane. For the problem of many non-support vectors and a few support vectors in the classification of SVM, a method to reduce the sa...
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