Proceedings ArticleDOI
Cognition-based contrast adjustment using neural network based face recognition system
Mitsuharu Matsumoto
- pp 3590-3594
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TLDR
Experimental results show that cognition-based evaluation has a potential to adjust the image contrast and this paper introduces a contrast adjustment using neural-network based face recognition system.Abstract:
This paper introduces a contrast adjustment using neural-network based face recognition system. Parameter setting problem is generally solved by maximization or minimization of some objective evaluation functions such as correlation and statistical independence. However, the tuned filter output is not always adequate for face recognition system because filter and face recognition system are separately tuned using different criterions. It is also difficult to set an objective criterion for parameter setting because there are no correct solutions when we consider contrast adjustment problem. To handle such cases, we look to some subjective information such as face in the image, and directly employ facial recognition system as evaluation function for parameter setting. Experimental results show that cognition-based evaluation has a potential to adjust the image contrast.read more
Citations
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TL;DR: This paper proposes a new method that utilizes Long Short-Term Memory units together with deep convolutional network to modelling the spatial correlations in texture image and results convince that the proposed model has stronger representation capacity for texture images and achieves better performance.
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