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Human computer interaction- applying fuzzy C-means, recurrent neural network and wavelet transforms for voluntary eye blink detection

机译:人机交互-应用模糊C均值,递归神经网络和小波变换进行自愿眨眼检测

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Eye blink Classification & latency computation is one of the interesting areas of the man-Machine interaction. However, overlapped eye blinks, whilst doing fast blinking, increase complexity of the system. In this paper, we developed a Neuro-Fuzzy system using Shift-Invariant Wavelet transforms to overcome this problem. It has been shown that our suggested procedure has high-resolution and is able to classify eye blinks and compute their latencies.
机译:眨眼分类和等待时间的计算是人机交互的有趣领域之一。但是,眨眼重叠,同时进行快速眨眼,会增加系统的复杂性。在本文中,我们开发了使用Shift不变小波变换的Neuro-Fuzzy系统,以克服此问题。已经表明,我们建议的过程具有高分辨率,并且能够对眨眼进行分类并计算其潜伏期。

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