Neural Computing and Applications: Volume 28 Issue 1, January 2017
Context of data points, which is usually defined as the other data points in a data set, has been found to paly important roles in data representation and classification. In this paper, we study the problem of using context of a data point for its classification problem. Our work is ...
Context, Nearest neighbors, Sparse regularization, Data representation, Pattern classification
Journal on Computing and Cultural Heritage (JOCCH): Volume 9 Issue 1, February 2016
Citation Count: 1
Downloads (6 Weeks): 4, Downloads (12 Months): 88, Downloads (Overall): 319
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By collecting images of heritage assets from members of the public and processing them to create 3D-reconstructed models, the HeritageTogether project has accomplished the digital recording of nearly 80 sites across Wales, UK. A large amount of data has been collected and produced in the form of photographs, 3D models, ...
crowd-sourced data, Automated photogrammetry
ISNN 2015: Proceedings of the 12th International Symposium on Advances in Neural Networks --- ISNN 2015 - Volume 9377
Publisher: Springer-Verlag New York, Inc.
In this paper, we study the problem of using contextual data points of a data point for its classification problem. We propose to represent a data point as the sparse linear reconstruction of its context, and learn the sparse context to gather with a linear classifier in a supervised way ...
Pattern classification, Nearest neighbors, Sparse regularization, Context learning
CW '14: Proceedings of the 2014 International Conference on Cyberworlds
Publisher: IEEE Computer Society
With the rise of digital content and web-based technologies, archaeologists and heritage organisations are increasingly striving to produce digital records of archaeology and heritage sites. The large numbers and geographical spread of these sites means that it would be too time-consuming for any one team to survey them. To meet ...
photogrammetry, co-production, archaeology