The prediction of protein structure that attracts many researchers to study is an NP-hard problem. In recent year, numerous algorithms are proposed. Although particle swarm optimizer has many advantages, the disadvant...
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DNA sequence encoding is significant for the improvement of reliability and validity of DNA computing. The hybridization reaction between DNA molecules is the most important and core reaction in the field of DNA compu...
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A novel image watermarking algorithm based on discrete wavelet transformation (DWT) and chaotic is proposed block the carrier image, scrambling and block the watermark image. First, randomly selected a block of carrie...
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Face recognition is an important research hotspot. More and more new methods have been proposed in recent years. In this paper, we propose a novel face recognition method which is based on PCA and logistic regression....
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Face recognition is an important research hotspot. More and more new methods have been proposed in recent years. In this paper, we propose a novel face recognition method which is based on PCA and logistic regression. PCA is one of the most important methods in pattern recognition. Therefore, in our method, PCA is used to extract feature and reduce the dimensions of process data. Afterwards, we present a novel classification algorithm and use logistic regression as the classifier for face recognition. The experimental results on two different face databases are presented to illustrate the efficacy of our proposed method.
Face recognition has become a research hotspot in the field of pattern recognition and artificial intelligence. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are two traditional methods in ...
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Face recognition has become a research hotspot in the field of pattern recognition and artificial intelligence. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are two traditional methods in pattern recognition. In this paper, we propose a novel method based on PCA image reconstruction and LDA for face recognition. First, the inner-classes covariance matrix for feature extraction is used as generating matrix and then eigenvectors from each person is obtained, then we obtain the reconstructed images. Moreover, the residual images are computed by subtracting reconstructed images from original face images. Furthermore, the residual images are applied by LDA to obtain the coefficient matrices. Finally, the features are utilized to train and test SVMs for face recognition. The simulation experiments illustrate the effectivity of this method on the ORL face database.
A kind of scale invariant features transformation (SIFT for short) operators on DWT domain are proposed for watermarking algorithm. Firstly, the low frequency of the image is obtained by DWT. And then the SIFT transfo...
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A kind of scale invariant features transformation (SIFT for short) operators on DWT domain are proposed for watermarking algorithm. Firstly, the low frequency of the image is obtained by DWT. And then the SIFT transformation is used to calculate the key feature points for the low frequency sub-image. Based on the chosen space's key points with moderate scale, a circular area as watermark embedding area is constructed. According to the research and final results, the novel digital watermark algorithm is proposed benefiting from the characteristics of SIFT's key points and local time-frequency of DWT. The algorithm not only has good robustness to resist on such operations as compression, shearing, noise addition, median filtering and scaling, but also has good inhibition to possible watermark fake verification.
Many machine learning algorithms have been applied to the problem of automatic emotion detection from speech. The k-nearest neighbor (KNN) is a popular learning algorithm for solving pattern recognition problem. Howev...
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To reveal the inner control mechanism of organism is an important content in the research of bioinformatics. The proliferation of a variety of high-throughput biological data for the reconstruction of gene regulatory ...
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In the acoustic scene classification task, the method of using mel-spectrogram to express the acoustic scene information is widely applied. However, mel-spectrogram has defects and it ignores important information abo...
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ISBN:
(纸本)9781450376570
In the acoustic scene classification task, the method of using mel-spectrogram to express the acoustic scene information is widely applied. However, mel-spectrogram has defects and it ignores important information about some acoustic scenes. The paper improves the mel-spectrogram and its generation algorithm. Including: I. For the sensitivity of the acoustic scene to high-frequency acoustic signals, the paper changes the filter design method of Mel Frequency Cepstrum Coefficient (MFCC). This method preserves more high frequency information by applying the equal-height triangular filter banks and increasing the number of the filters. II. Based on the previous step, an enhancement algorithm is proposed for the problem of the lack of high-frequency weak signals in the characteristic spectrum. The algorithm performs nonlinear mapping on the mel-spectrogram, which makes the transformed high-frequency weak signal feature information more obvious. The algorithm is verified by DCASE 2018 acoustic scene classification dataset and LITIS ROUEN dataset. The experimental results demonstrate the effectiveness of the proposed algorithm.
A new image fusion encryption algorithm based on image fusion and DNA sequence operation and hyper-chaotic system is presented. Firstly, two DNA sequences matrices are obtained by encoding the original image and the k...
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A new image fusion encryption algorithm based on image fusion and DNA sequence operation and hyper-chaotic system is presented. Firstly, two DNA sequences matrices are obtained by encoding the original image and the key image. Secondly, using the chaotic sequences generated by Chen's hyper-chaotic maps to scramble the locations of elements from the DNA sequence matrix which generated form original image. Thirdly, XOR the scrambled DNA matrix and the random DNA matrix by using DNA sequence addition operation. At last, decoding the DNA sequence matrix, we will get the encrypted image. The simulation experimental results and security analysis show that our algorithm not only has good encryption effect, but also has the ability of resisting exhaustive attack and statistical attack.
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