Global k-NN Classifier for Small Sample Size Problems - Zhang, Nan
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What is Small Sample Size Problem? The methods need training samples to learn the information of the data. Some kind of data is high-dimensional, but no enough samples can be collected. When the number of training samples is much smaller than the dimension of data, we called this Small Sample Size Problem. In the face recognition field, small sample size problems generally exist.Let's talk about how to solve this problem better.

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Produktbeschreibung
What is Small Sample Size Problem? The methods need training samples to learn the information of the data. Some kind of data is high-dimensional, but no enough samples can be collected. When the number of training samples is much smaller than the dimension of data, we called this Small Sample Size Problem. In the face recognition field, small sample size problems generally exist.Let's talk about how to solve this problem better.
Autorenporträt
Zhang, Nan
Nan Zhang received the Ph.D. degree in pattern recognition and intelligence system from Nanjing University of Science and Technology (NUST) in 2013. She is currently a Lecturer with Control Technology Institute, Wuxi Institute of Technology. Her current research interests include pattern recognition, computer vision and machine learning.