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Thus, the proposed BLPP utilizes both the spatial information and the image content information, which results in higher recognition rate.
The results indicate that the proposed approach has a higher recognition rate than other methods on the same dataset.
Experimental results show that our new immune convolutional neural network has higher recognition rate, more stable performance and faster computing speed than the traditional convolutional neural network.
The experimental results of verification on Hong Kong Polytechnic University Palmprint Database show that the proposed approach has higher recognition rate and faster processing speed.
Experiments show that our approach outperforms state-of-the-art methods, and obtains a higher recognition rate without sacrificing precision both at high FP rates and high occlusion rates.
Compared to the single classifier based recognition processes, HPSMCF has higher recognition rate.
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One survey claimed he had a higher recognition rating than the Chancellor, Norman Lamont.
Our evaluation with two databases shows that fusing image-based and temporal features yields higher recognition rates.
Experimental results show that the DuoNN architecture, configuration, and the additional emotional information processing, yield higher recognition rates and faster learning and decision making.
Experimental results on various public face databases demonstrate that the proposed algorithm provides a better feature representation for classification and achieves higher recognition rates compared with several state-of-the-art algorithms.
Most of the algorithms tend to get higher recognition rates when the subspace dimension increases.
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