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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

共 1406 条记录，以下是361-370 订阅

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Ligand Electron Density Shape recognition Using 3D Zernike Descriptors

Ligand Electron Density Shape Recognition Using 3D Zernike D...

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4th international conference pattern recognition in bioinformatics

作者： Gunasekaran, Prasad Grandison, Scott Cowtan, Kevin Mak, Lora Lawson, David M. Morris, Richard J. John Innes Ctr Dept Computat & Syst Biol Norwich Res PkColney Lane Norwich NR4 7UH Norfolk England Univ York Dept Chem Struct Biol Lab York YO10 5DD N Yorkshire England Inst Food Res Theoret Syst Biol Norwich NR4 7UA Norfolk England John Innes Ctr Dept Biol Chem Norwich NR4 7UH Norfolk England

ISBN: (纸本)9783642040306

We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomials) and the coefficients from this expansion are employed to construct rotation-invariant descriptors. these descriptors can be compared highly efficiently against large databases of descriptors computed front other molecules. In this manuscript we describe this process and show initial results from an electron density interpretation study oil a dataset containing over a hundred OMIT maps. We could identify the correct ligand as the first hit in about 30% of the cases, within the top five in a further 30% of the cases, and giving rise to an 80% probability of getting the correct ligand within the top ten matches. In all but a few examples, the top hit was highly similar to the correct ligand in both shape and chemistry. Further extensions and intrinsic limitations of the method are discussed.

关键词： pattern recognition structural bioinformatics electron density protein crystallography 3D Zernike moments

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Finger Movement recognition for Virtual Keyboard Based on sEMG 5

Finger Movement Recognition for Virtual Keyboard Based on sE...

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5th international conference on Imaging, Signal Processing and Communications (ICISPC)

作者： Li, Longfei An, Xuanyu Geng, Danlei Qin, Shiyi Shen, Sheng Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710121 Peoples R China Univ Leeds Sch Elect & Elect Engn Woodhouse Lane Leeds LS2 9JT W Yorkshire England Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian 710121 Peoples R China Xidian Univ Sch Commun & Informat Engn Xian 710121 Peoples R China Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93107 USA

ISBN: (纸本)9781665424257

Disabled forelimb has been a main obstacle for people to communicate with computer by keyboard. To achieve the interface with computer, most of them have to use voice commands to interact with it. But this kind of interface has many inconveniences, such as the inability of using it in both noisy and quiet places as well as inadequate provision of commands compared to keyboard. Surface electromyography (sEMG)is a kind of signal that is created when muscles start to contract or the brain produces nerve impulses for muscle contraction. Also the existence of sEMG signals does not depend on the integrity of hands. this project aims to explore the possibility of exploiting sEMG signals to realize that the disabled can interact with the computer through the keyboard. We designed a series of hand movements (sEMG signals) and made them correspond one-to-one with specific strings. By detecting and recognizing the sEMG signals of muscles, the disabled can use the virtual keyboard to interact with the computer normally. In addition, we also designed a signal processing method based on multi-class support vector machine (SVM) with error-correcting output code (ECOC) and label-threshold pre-process. It helps patients in need create their own sEMG signal recognition model. Traditional signal processing method with floating window can accurately identify each action, but it will output the classification results of each action several times, which will cause great inconvenience to the use of the virtual keyboard. this new signal processing method with ECOC and pre-process greatly avoids this problem.

关键词： virtual keyboard SVM sEMG pattern recognition

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Research on PD pattern recognition by extracting features from PD energy distribution 5

Research on PD pattern recognition by extracting features fr...

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5th international conference on Electrical Machines and Systems

作者： Li, X Sun, CX Yang, YM Li, J Tang, JJ Minist Educ Key Lab High Voltage Engn & Elect New Technol Chongqing 400044 Peoples R China

this paper studies the characteristics of denoised partial discharge (PD) signals and then puts forward a new method to extract features from distribution of PD energy against relevant phase position. the analysis res... 详细信息

ISBN: (纸本)7506251159

关键词： partial discharge energy feature partial discharge types recognition

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Requirements for a behaviour pattern based assistant for early detection and management of neurodegenerative diseases

Requirements for a behaviour pattern based assistant for ear...

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2011 5th international conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2011

作者： Hochgatterer, Andreas Roedl, Lukas Martineź, Alberto Etxeberria, Igone Aldaz, Erkuden Wöckl, Bernhard Bund, Jürgen Health and Environment Department AIT Austrian Institute of Technology GmbH Wiener Neustadt Austria Health and Quality of Life TECNALIA Research and Innovation Zamudio Spain INGEMA Instituto Gerontológico Matia San Sebastián Spain CURE Center for Usability Research and Engineering Vienna Austria Meticube-Software Coimbra Portugal

ISBN: (纸本)9781936968152

this paper describes the various aspects of the BEDMOND AAL Joint Programme project, which aims at the development of an ICT-based system for the early detection of Alzheimer's disease and other neurodegenerative diseases, with focus on the identified applied reasoning layers. First the requirements of such a behaviour pattern based assistant are discussed, then the used system architecture is introduced and finally the applied reasoning layers for the situation recognition, interpretation and data representation layers are also detailed. © 2011 ICST.

关键词： Neurodegenerative diseases

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Facial Expression recognition with Local Binary pattern and Laplacian Eigenmaps

Facial Expression Recognition with Local Binary Pattern and ...

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5th international conference on Intelligent Computing

作者： Ying, Zilu Cai, Linbo Gan, Junying Hey, Sibin Wuyi Univ Sch Informat Jiangmen 529020 Guangdong Peoples R China

ISBN: (纸本)9783642040696

A new approach to facial expression recognition is constructed by combining the Local Binary pattern and Laplacian Eigenmaps. Firstly, each image is transformed by an LBP operator and then divided into 3x5 non-overlapping blocks. the features of facial expression images are formed by concatenating the LBP histogram of each block. Secondly, linear graph embedding framework is used as a platform, and then Laplacian Eigenmaps is developed under this framework and applied for feature dimensionality reduction. Finally, Support Vector Machine is used to classify the seven expressions (anger, disgust, fear, happiness, neutral, sadness and Surprise) on JAFFE database. the maximum facial expression recognition rate of the proposed algorithm reaches to 70.48% for person-independent recognition, which is much better than that of LBP+PCA and LBP+LDA algorithms. the experiment results prove that the facial expression recognition with local binary pattern and Laplacian Eigenmaps is an effective and feasible algorithm.

关键词： Facial expression recognition Local binary pattern Graph embedding Laplacian Eigenmaps

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Outdoor scenes interpretation suitable for blind people navigation

Outdoor scenes interpretation suitable for blind people navi...

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Proceedings of the 5th international conference on Image Processing and its Applications

作者： Mecocci, A. Lodola, R. Salvatore, U. Univ of Pavia Pavia Italy

An important problem for blind people during their navigation in the outdoor environment is the need for external help while reaching a specific place. In order to reduce this dependence, a smart mobile system capable of simple scene descriptions and useful landmarks should be developed. this study proposes a system that provides an interpretation of real scenes through single (monocular) image analysis. the efficiency and effectiveness of the proposed system is validated using Indoor and Outdoor scenes in natural situations without any expedient to make image interpretation easier.

关键词： pattern recognition systems

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Improving spectral image classifications by incorporating context data using likelihood vectors

Improving spectral image classifications by incorporating co...

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Proceedings of the 5th international conference on Image Processing and its Applications

作者： Gorte, B.G.H. Int Inst for Aerospace Survey and Earth Sciences Netherlands

the objective of this study is to find an appropriate method of improving spectral image classifications. To fulfill this objective, a slightly modified k-Nearest-Neighbour strategy is proposed for the calculation of feature-probability densities. In addition, the method of using spatially distributed prior probabilities is reviewed and shown how it can be perfectly combined with the proposed method. By conducting several experiments, it is found that the proposed strategy serves the purpose of accurately estimating class-areas, as well as increasing classification accuracies to the same extent as the 'pixel prior' method does.

关键词： pattern recognition

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5th Asian conference on pattern recognition, ACPR 2019

5th Asian Conference on Pattern Recognition, ACPR 2019

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5th Asian conference on pattern recognition, ACPR 2019

ISBN: (纸本)9783030412982

the proceedings contain 123 papers. the special focus in this conference is on pattern recognition. the topics include: Continual Learning of Image Translation Networks Using Task-Dependent Weight Selection Masks;a Real-Time Eye Tracking Method for Detecting Optokinetic Nystagmus;network Structure for Personalized Face-Pose Estimation Using Incrementally Updated Face-Shape Parameters;optimal Rejection Function Meets Character recognition Tasks;comparing the recognition Accuracy of Humans and Deep Learning on a Simple Visual Inspection Task;improved Gamma Corrected Layered Adaptive Background Model;one-Shot Learning-Based Handwritten Word recognition;first-Person View Hand Parameter Estimation Based on Fully Convolutional Neural Network;dual-Attention Graph Convolutional Network;enhancing Open-Set Face recognition by Closing It with Cluster-Inferred Gallery Augmentation;chart-Type Classification Using Convolutional Neural Network for Scholarly Figures;handwritten Digit String recognition for Indian Scripts;spatial-Temporal Graph Attention Network for Video-Based Gait recognition;supervised Interactive Co-segmentation Using Histogram Matching and Bipartite Graph Construction;Using Deep Convolutional LSTM Networks for Learning Spatiotemporal Features;two-Stage Fully Convolutional Networks for Stroke Recovery of Handwritten Chinese Character;text Like Classification of Skeletal Sequences for Human Action recognition;Background Subtraction Based on Encoder-Decoder Structured CNN;multi Facet Face Construction;Automated 2D Fetal Brain Segmentation of MR Images Using a Deep U-Net;action recognition in Untrimmed Videos with Composite Self-attention Two-Stream Framework;EEG Representations of Spatial and Temporal Features in Imagined Speech and Overt Speech;GAN-based Abnormal Detection by Recognizing Ungeneratable patterns;modality-Specific Learning Rate Control for Multimodal Classification;3D Multi-frequency Fully Correlated Causal Random Field Texture Model;meaning Guided

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An implementation of postal numerals segmentation and recognition system for Chinese business letters 5

An implementation of postal numerals segmentation and recogn...

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5th international conference on Document Analysis and recognition, ICDAR 1999

作者： Lu, Yue Shi, Pengfei Wu, Jianzhong Rui, Jianming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200030 China Third Research Institute Ministry of Post and Telecommunication Shanghai200062 China

ISBN: (纸本)0769503187

In this paper, a practical postal numeral segmentation and recognition system for Chinese business letters is presented. Line information for the address blocks is gained from the envelope image by projection, then the sub-image of the postal numerals is segmented. the numerals are recognized by three independent classifiers, and their results are combined to form final results. An improved voting principle based on a priori knowledge of each classifier is utilized to combine multiple classifiers in order to achieve perfect performance for high recognition rate and low error rate. the recognition ability of each classifier, acting with the voting principle, is obtained by statistics for a large set of samples. Different thresholds gained by training are employed for different classes, which can yield better results. A parallel structure hardware is designed to implement a real-time image processing system. the performance of the system is shown to be satisfactory, sufficient for the requirements of practical use. © 1999 IEEE.

关键词： Real time systems

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CTC - Correlating tree patterns for classification

CTC - Correlating tree patterns for classification

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5th IEEE international conference on Data Mining

作者： Zimmermann, A Bringmann, B Univ Freiburg Machine Learning Lab D-79110 Freiburg Germany

ISBN: (纸本)0769522785

We present CTC, a new approach to structural classification. It uses the predictive power of tree patterns correlating with the class values, combining state-of-the-art tree mining with sophisticated pruning techniques to find the k most discriminative pattern in a dataset. In contrast to existing methods, CTC uses no heuristics and the only parameters to be chosen by the user are the maximum size of the rule set and a single, statistically well founded cut-off value. the experiments show that CTC classifiers achieve good accuracies while the induced models are smaller than those of existing approaches, facilitating comprehensibility.

关键词： pattern recognition

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