Results 291 to 300 of about 812,194 (338)

Introducing Domain Knowledge

2020
In this chapter we will consider another application case of Deep learning: classification of brain images for detection of Alzheimer’s disease. In this particular application of medical imaging domain, Deep NNs have become the mandatory tool. In this chapter we give some highlights on how the usual steps in design of a Deep Neural Network classifier ...
Akka Zemmari, Jenny Benois-Pineau
openaire   +1 more source

Seismic Dip Estimation With a Domain Knowledge Constrained Transfer Learning Approach

IEEE Transactions on Geoscience and Remote Sensing, 2022
Accurate estimation of volumetric seismic dip is of great significance for subsequent seismic processing and interpretation works. Recently, with the development of deep learning techniques, convolutional networks are also applied for seismic dip ...
Y. Ao, Wen-kai Lu, P. Xu, B. Jiang
semanticscholar   +1 more source

Happiness Prediction With Domain Knowledge Integration and Explanation Consistency

IEEE Transactions on Computational Social Systems
Happiness prediction based on large-scale online data and machine learning models is an emerging research topic that underpins a range of issues, from personal growth to social stability.
Xiaohua Wu, Lin Li, Xiaohui Tao, Frank Xing, Jingling Yuan   +4 more
semanticscholar   +1 more source

Visualizing knowledge domains

Annual Review of Information Science and Technology, 2003
L'A. passe en revue les techniques de visualisation utilisees pour representer de facon cartographique la structure de domaine des disciplines scientifiques, et pour soutenir la recherche d'information et la classification. Un bref historique montre que la visualisation des domaines de connaissances s'enracine dans des disciplines telles que la ...
Katy Börner, Chaomei Chen, Kevin W. Boyack   +2 more
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Using domain knowledge in knowledge discovery

Proceedings of the eighth international conference on Information and knowledge management, 1999
With the explosive growth of the size of databases, many knowledge discovery applications deal with large quantities of data. There is an urgent need to develop methodologies which will allow the applications to focus search to a potentially interesting and relevant portion of the data, which can reduce the computational complexity of the knowledge ...
Suk-Chung Yoon, Lawrence J. Henschen, E. K. Park, Sam Makki   +3 more
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Domain Knowledge Integration

2010
In this chapter we focus on the theoretical underpinning and enabling technologies which ensure that the knowledge about the domain embedded in the software system remains current and is understood by the members of the VE.
Stalker, Iain Duncan, Carpenter, Martin, Mehandjiev, N, Owrak, Ali, Weichhart, Georg   +4 more
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Visualizing the WCCI 2006 Knowledge Domain

2006 IEEE International Conference on Fuzzy Systems, 2006
In this paper, a knowledge domain visualization approach is applied to the computational intelligence held. A so-called concept map based on the abstracts of the papers presented at the WCCI 2006 is constructed and analyzed. The concept map provides an overview of the computational intelligence field by visualizing the associations between the field's ...
Eck, van, N.J.P., Waltman, L.R., Berg, van den, J., Kaymak, U.   +3 more
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Applying domain knowledge to knowledge discovery

2023
The amount of data being collected and stored in databases is increasing constantly, because of this the process of knowledge discovery can and will become increasingly time consuming. This thesis researches and shows the advantages of applying previous knowledge about the data, known as domain knowledge, to a data set being analyzed when running ...
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OnlineAugment: Online Data Augmentation with Less Domain Knowledge

European Conference on Computer Vision, 2020
Data augmentation is one of the most important tools in training modern deep neural networks. Recently, great advances have been made in searching for optimal augmentation policies in the image classification domain.
Zhiqiang Tang, Yunhe Gao, Leonid Karlinsky, P. Sattigeri, R. Feris, Dimitris N. Metaxas   +5 more
semanticscholar   +1 more source

Knowledge acquisition from corresponding domain knowledge transformations

2009 IEEE International Conference on Information Reuse & Integration, 2009
The capability to efficiently retrieve knowledge in response to specific user queries offers the potential to create decision support systems of unprecedented utility, i.e., systems which can accelerate the learning process. This paper presents such an architecture, the Type 2 Knowledge Amplification by Structured Expert Randomization (T2K) system ...
Michael Armella, Isai Michel Lombera, Stuart H. Rubin, Shu-Ching Chen, Gordon Lee   +4 more
openaire   +1 more source