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5th International Symposium on IT in Medicine and Education, ITME 2013

作者： Junyan, Zhang Chenhui, Yang Information Science and Technology College Chengdu University Chengdu China Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan Chengdu University Chengdu China

ISBN: (纸本)9789400776173

pattern matching is a fundamental application in biomedicine and biological sequence analysis. A wildcard can match any one character in a sequence. Multiple wildcards form a gap. A flexible wildcard gap can match any characters with specific length which is specified by users. Therefore, the effective algorithm performing this kind of matching is in great need. In this paper, we design PMFG algorithm and achieve it by dividing a pattern into multiple sub-patterns with different length based on gap segmentation. After computing the starting positions and ending positions of each subpattern, the effective intervals and effective starting positions can be determined one by one. The number of the elements in the last effective position set equals to the number of the matching. A comparison experiments are done based on three DNA sequences. The results show that PMFG algorithm has better performance in the same fields. © Springer Science+Business Media Dordrecht 2014.

关键词： pattern matching

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Contour extraction model introducing contrast adaptive characteristics based on visual pathway

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Multimedia Tools and Applications 2024年第15期84卷 14693-14717页

作者： Fang, Tao Cai, Zhefei Fan, Yingle College of Electronics and Information Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Hangzhou310027 China Laboratory of Pattern Recognition and Image Processing Hangzhou Dianzi University Hangzhou310018 China

Effectively extracting image subject contours holds significant importance for subsequent image processing tasks. Recognizing the pivotal role of contrast features in contour characterization, this paper proposes a novel contour extraction model with contrast adaptive characteristics, inspired by visual perception simulation visual pathways. Firstly, leveraging the color antagonism traits of retinal ganglion cells, we construct a color image contrast calculation model to enhance the representation of visual information contrast. Furthermore, drawing upon the feed-forward impact of the retina on Lateral Geniculate Nucleus (LGN) cells, we introduce a contrast gain control mechanism to extract multi-directional primary contour responses. Secondly, employing the LIF neuron network to simulate the lateral geniculate body's information flow processing mechanism, we encode visual information via pulse firing to eliminate redundant contour details. Then, by considering the primary visual cortex (V1) cell's receptive field size variation with contrast, we devise a contrast-adaptive dynamic receptive field model. Additionally, we develop a texture suppression model based on the orientation/contrast disparity between the receptive field model's center and periphery. Finally, integrating the primary contour response and the image obtained through the inhibition model, we fuse features to derive the final image subject target contour. This study employs the BSDS500 dataset and the RuG40 dataset for experimentation. Comparative analysis against mainstream methods demonstrates our approach's superior ability to retain the main image outline while suppressing non-edge textures, with P-value indicators for contour detection of 0.58 and 0.50, respectively. Furthermore, visual analysis using box and whisker plots confirms the robustness of our proposed method. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Textures

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Image recognition Based on Combined Filters with Pseudoinverse Learning Algorithm 15th

Image Recognition Based on Combined Filters with Pseudoinver...

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15th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2019

作者： Deng, Xiaodan Sun, Xiaoxuan Guo, Ping Yin, Qian Image Processing and Pattern Recognition Laboratory School of Systems Science Beijing Normal University Beijing100875 China Image Processing and Pattern Recognition Laboratory College of Information Science and Technology Beijing Normal University Beijing China

ISBN: (纸本)9783030198220

Deep convolution neural network (CNN) is one of the most popular Deep neural networks (DNN). It has won state-of-the-art performance in many computer vision tasks. The most used method to train DNN is Gradient descent-based algorithm such as Backpropagation. However, backpropagation algorithm usually has the problem of gradient vanishing or gradient explosion, and it relies on repeated iteration to get the optimal result. Moreover, with the need to learn many convolutional kernels, the traditional convolutional layer is the main computational bottleneck of deep CNNs. Consequently, the current deep CNN is inefficient on computing resource and computing time. To solve these problems, we proposed a method which combines Gabor kernel, random kernel and pseudoinverse kernel, incorporating with pseudoinverse learning (PIL) algorithm to speed up DNN training processing. With the multiple fixed convolution kernels and pseudoinverse learning algorithm, it is simple and efficient to use the proposed method. The performance of the proposed model is tested on MNIST and CIFAR-10 datasets without using GPU. Experimental results show that our model is better than existing benchmark methods in speed, at the same time it has the comparative recognition accuracy. © 2019, IFIP International Federation for information processing.

关键词： Image recognition

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Applications of artificial intelligence to lipid nanoparticle delivery

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Particuology 2024年第7期90卷 88-97页

作者： Ye Yuan Yuqi Wu Jiabei Cheng Kaiyuan Yang Yilin Xia Hongguang Wu Xiaoyong Pan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaChina Songjiang Research Institute Songjiang District Central HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.

关键词： Artificial intelligence Lipid nanoparticles Antibody Targeted conjugation

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Multi-view face detection based on multi-features adaboost collaborative learning algorithm

Multi-view face detection based on multi-features adaboost c...

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2014 International Conference on Applied Sciences, Engineering and Technology, ICASET 2014

作者： Huang, Rong Bing Zhang, Hong Shu, Chang Ming Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan Chengdu University Sichuan 610106 China School of Information Science and Technology Chengdu University Sichuan 610106 China

ISBN: (纸本)9783038351849

In view of the multi-view face detection problem under complex background, an improved face detection method based on multi-features boosting collaborative learning algorithm integrating local binary pattern (LBP) is presented. Firstly, facial skin color information is used to exclude most of the background regions. Then, Haar-like feature and LBP feature are extracted from facial candidate regions and inputted into a modified AdaBoost algorithm to obtain a strong classifier. Lastly, in order to improve the detection speed, pyramid classifier system structure is adopted to determine the face. The experimental results on CMU standard test set and life photos, the proposed method has achieved the rapid detection of multi-view face image. © (2014) Trans Tech Publications, Switzerland.

关键词： Face recognition

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Study of the 6.x nm short wavelength radiation spectra of laser-produced erbium plasmas for BEUV lithography

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Plasma Science and Technology 2023年第6期25卷 41-51页

作者：吴涛王倩陈柳安陆培祥 Hubei Key Laboratory of Optical Information and Pattern Recognition School of Optical Information and Energy EngineeringWuhan Institute of TechnologyWuhan 430205People's Republic of China Guangdong Intelligent Robotics Institute Dongguan 523808People's Republic of China

Beyond extreme ultraviolet(BEUV)radiation with a wavelength of 6.x nm for lithography is responsible for reducing the source wavelength to enable continued miniaturization of semiconductor *** this work,the Required BEUV light at 6.x nm wavelength was generated in dense and hot Nd:YAG laser-produced Er *** spectral contributions from the 4p–4d and 4d–4f transitions of singly,doubly and triply excited states of Er XXIV–Er XXXII in the BEUV band were calculated using Cowan and the Flexible Atomic *** was also found that the radiative transitions between multiply excited states dominate the narrow wavelength window around 6.x *** the assumption of collisional radiative equilibrium of the laser-produced Er plasmas,the relative ion abundance in the experiment was *** the Boltzmann quantum state energy level distribution and Gram–Charlier fitting function of unresolved transition arrays(UTAs),the synthetic spectrum around 6.x nm was finally obtained and compared with the experimental *** spatio-temporal distributions of electron density and electron temperature were calculated based on radiation hydrodynamic simulation in order to identify the contributions of various ionic states to the UTAs arising from the Er plasmas near 6.x nm.

关键词： laser-produced plasmas unresolved transition array collisional radiative equilibrium

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An efficient multiparty quantum secret sharing scheme using a single qudit

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Chinese Physics B 2023年第8期32卷 161-170页

作者：胡文文熊邦书周日贵 School of Information Engineering Nanchang Hangkong UniversityNanchang 330063China Key Laboratory of Image Processing and Pattern Recognition of Jiangxi Province Nanchang Hangkong UniversityNanchang 330063China College of Information Engineering Shanghai Maritime UniversityShanghai 201306China

The aim of quantum secret sharing,as one of most promising components of quantum cryptograph,is one-tomultiparty secret communication based on the principles of quantum *** this paper,an efficient multiparty quantum secret sharing protocol in a high-dimensional quantum system using a single qudit is *** participant's shadow is encoded on a single qudit via a measuring basis encryption method,which avoids the waste of qudits caused by basis *** analysis indicates that the proposed protocol is immune to general attacks,such as the measure-resend attack,entangle-and-measure attack and Trojan horse *** to former protocols,the proposed protocol only needs to perform the single-qudit measurement operation,and can share the predetermined dits instead of random bits or dits.

关键词： quantum secret sharing high-dimensional measurement basis encrypted security analysis

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AMCF-Net: A Novel Adaptive Multi-Channel Fusion Network for Computer-Aided Diagnosis of Lung Nodules in Chest Computed Tomography

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IET Communications 2025年第1期19卷

作者： Nan Wang Yu Gu Lidong Yang Baohua Zhang Jing Wang Xiaoqi Lu Jianjun Li Dahua Yu Ying Zhao Xin Liu Siyuan Tang Qun He Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Digital and Intelligent Industry Inner Mongolia University of Science and Technology Baotou China School of Information and Electronics Beijing Institute of Technology Beijing China College of Information Engineering Inner Mongolia University of Technology Hohhot China School of Computer Science and Technology Baotou Medical College Inner Mongolia University of Science and Technology Baotou China

Malignant lung nodules can significantly affect patients' normal lives and, in severe cases, threaten their survival. Owing to the heterogeneity of computed tomography scans and the varying sizes of nodules, physicians often face challenges in diagnosing this condition. Therefore, a novel adaptive multi-channel fusion network (AMCF-Net) is proposed for computer-aided diagnosis of lung nodules. First, a Multi-Channel Fusion Model module is designed, which divides the channels into two parts in specific proportions, effectively extracting multi-scale channel information while reducing network parameters. After the feature maps output at each layer of the AMCF-Net, a novel adaptive depth-wise separable convolution with a squeeze-and-excitation module is designed to adaptively integrate the feature maps of various stages of the AMCF-Net, ensuring that the key lesions of lung nodules are not lost during classification. Finally, a hybrid loss scheme based on an adaptive mixing ratio is proposed to solve the problem of an imbalanced number of positive and negative nodule samples in the dataset. The model achieved the following test results: an accuracy of 90.22%, a specificity of 98.19%, an F1-score of 86.57%, a sensitivity of 86.49%, and a G-mean of 87.72%. Compared with other advanced networks, AMCF-net delivers high-precision lung nodule classification with minimal inference cost. Related codes have been released at: https://***/GuYuIMUST/AMCF-net .

关键词： computer networks convolution health care image processing neural nets

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Steganography algorithm for adaptive multi-rate wideband speech based on algebraic codebook search

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The Journal of China Universities of Posts and Telecommunications 2018年第3期25卷 71-79页

作者： Ruan Ye Xu Yanyan Ke Dengfeng Su Kaile School of Information Science and Technology Beijing Forestry University National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of Sciences Institute for Integrated and Intelligent Systems Griffith University College of Information Science and Technology Jinan University

With the popularity of adaptive multi-rate wideband （AMR-WB） audio in mobile communication, many AMR- WB based techniques, such as a similar compression architecture to transmit secret information during the process of compression, were proposed to transmit covert messages. However, if a sender does not have the original waveform audio format （WAV） audio, the architecture cannot be used. In this paper, a new covert message method, which takes effect after WAV audio is compressed into AMR-WB speech, is proposed. This method takes advantage of algebraic codebook search. Aiming at improving speed and reducing search space, it does not perform algebraic codebook search using the optimal search algorithm, and it does not reach the positions of non-zero pulses via depth-first tree search that characterizes the energy of audio. According to the features of search methods and the codebook index construction, every track in each subframe is analyzed to find the proper positions for embedding secret information. Experimental results show that the proposed method has satisfactory capacity and simplicity regardless of compression process.

关键词： steganography algorithm WAV audio compressed audio adaptive multi-rate wideband speech

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Dynamic Action recognition under Simulated Prosthetic Vision

Dynamic Action Recognition under Simulated Prosthetic Vision

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2020 International Conference on Networking and Network Applications, NaNA 2020

作者： Zhao, Ying Xu, Dantong Wang, Tie Ren, Yanchun Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia

ISBN: (纸本)9781728189543

Purpose. To assess the recognition pattern of dynamic action by visual prosthesis' wearers. Methods. Twenty volunteers (classified by gender and experience) were recruited to carried out action recognition test in simulated prosthetic vision. Twenty-three common dynamic actions video clips usually see in daily life were selected and formed the experimental action set which was divided into three parts including combined actions, simple actions and difficult actions in turn. The action animations made by 3D Studio Max were recorded by Banicam to convert to MP4 video format and processed to phosphene video clips by MATLAB in different resolutions (16 × 16, 24 × 24, 32 × 32, 48 × 48, 64 × 64, 128 × 128). Result. Comparing the recognition results, male group and female group had no significant difference. 48 × 48 resolution was the considerable latent capacity which subjects had stable performance. After a period of study, the performance of prosthesis wearers could be improved significantly. © 2020 IEEE.

关键词： MATLAB

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