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检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics"

共 1869 条记录，以下是501-510 订阅

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EMG pattern recognition using decomposition techniques for constructing multiclass classifiers

EMG pattern recognition using decomposition techniques for c...

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IEEE/RAS-EMBS international conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Huaiqi Huang Tao Li Claudio Bruschini Christian Enz Volker M. Koch Jörn Justiz Christian Antfolk BME Lab Bern University of Applied Sciences Biel Switzerland Ecole Polytechnique Fédérale de Lausanne (EPFL) Integrated Circuits Laboratory Neuchâtel Switzerland Department of Biomedical Engineering Lund University Lund Sweden

ISBN: (纸本)9781509032884

To improve the dexterity of multi-functional myoelectric prosthetic hand, more accurate hand gesture recognition based on surface electromyographic (sEMG) signal is needed. this paper evaluates two types of time-domain EMG features, one independent feature and one combined feature including four features. the selected features from eight subjects with 13 finger movements were tested with four decomposed multi-class support vector machines (SVM), four decomposed linear discriminant analyses (LDA) and a multi-class LDA. the classification accuracy, training, and classification time are compared. the results have shown that the combined features decrease error rate, and binary tree based decomposition multiclass classifiers yield the highest classification success rate (88.2%) with relatively low training and classification time.

关键词： Support vector machines Electromyography Training Electrodes Kernel Prosthetics Muscles

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A novel hybrid CNN-AIS visual pattern recognition engine 6th

A novel hybrid CNN-AIS visual pattern recognition engine

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6th international conference on pattern recognition and Machine Intelligence, PReMI 2015

作者： Bhalla, Vandna Chaudhury, Santanu Jain, Arihant Indian Institute of Technology Delhi New Delhi India

Machine learning methods are used today mostly for recognition problems. Convolutional Neural Networks (CNN) have time and again proved successful for many image processing tasks primarily for their architecture. In this paper we propose to apply CNN to small data sets like for example, personal photo albums or other similar environs where the size of training dataset is a limitation, within the framework of a proposed hybrid CNN-AIS model. We use Artificial Immune System Principles to enhance the small size of training data set. A layer of Clonal Selection is added to the local filtering and max pooling of CNN Architecture. the proposed Architecture is evaluated using the standard MNIST dataset by limiting the data size and also with a small personal data sample belonging to two different classes. Experimental results show that the proposed hybrid CNN-AIS based recognition engine works well when the size of training data is limited in size. © Springer international Publishing Switzerland 2015.

关键词： Neural networks

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Extracting key challenges in achieving sobriety through shared subspace learning 12th

Extracting key challenges in achieving sobriety through shar...

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12th international conference on Advanced Data Mining and Applications, ADMA 2016

作者： Harikumar, Haripriya Nguyen, thin Rana, Santu Gupta, Sunil Kaimal, Ramachandra Venkatesh, Svetha Centre for Pattern Recognition and Data Analytics Deakin University Geelong Australia Computer Science and Engineering Department Amrita University Kollam India

ISBN: (纸本)9783319495859

Alcohol abuse is quite common among all people without any age restrictions. the uncontrolled use of alcohol affects both the individual and society. Alcohol addiction leads to a huge increase in crime, suicide, health related problems and financial crisis. Research has shown that certain behavioral changes can be effective towards staying abstained. the analysis of behavioral changes of quitters and those who are at the beginning phase of quitting can be useful for reducing the issues related to alcohol addiction. Most of the conventional approaches are based on surveys and, therefore, expensive in both time and cost. Social media has lend itself as a source of large, diverse and unbiased data for analyzing social behaviors. Reddit is a social media platform where a large number of people communicate with each other. It has many different sub-groups called subreddits categorized based on the subject. We collected more than 40,000 self reported user’s data from a subreddit called ‘/r/stopdrinking’. We divide the data into two groups, short-term with abstinent days less than 30 and long-term abstainers with abstinent days greater than 365 based on badge days at the time of post submission. Common and discriminative topics are extracted from the data using JS-NMF, a shared subspace non-negative matrix factorization method. the validity of the extracted topics are demonstrated through predictive performance. © Springer international Publishing AG 2016.

关键词： Non-negative matrix factorization

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Development and preliminary testing of a flexible control system for powered knee-ankle prostheses

Development and preliminary testing of a flexible control sy...

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IEEE/RAS-EMBS international conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Ann M. Simon Kimberly A. Ingraham John A. Spanias Aaron J. Young Levi J. Hargrove Department of Physical Medicine and Rehabilitation Northwestern University Chicago IL USA Rehabilitation Institute of Chicago Chicago IL USA Department of Mechanical Engineering University of Michigan Ann Arbor MI USA Department of Biomedical Engineering Northwestern University Evanston IL USA Human Neuromechanics Laboratory University of Michigan Ann Arbor MI USA

ISBN: (纸本)9781509032884

Recently developed motorized lower limb prostheses which provide joint power at the knee and/or ankle have been shown to assist users in performing a variety of ambulation tasks. Control of these devices, specifically creating seamless, natural, and accurate mode transitions, is challenging. the control system also needs to allow users the flexibility to perform these tasks with a wide range of variability. the goal of this study was to develop and test a flexible control system for a powered knee-ankle prosthesis. Specifically, a pattern recognition system was trained to recognize the transitions between six modes (standing, level-ground walking, ramp ascent, ramp descent, stair ascent, and stair descent) at various discrete time points during the gait cycle. Six transfemoral users were successful performing a variety of ambulation tasks including climbing a 3- and 4-step staircases, performing walking and standing transitions to and from the staircases, approaching the stairs and ramps at various angles, and ambulating at various speeds. Offline classification results demonstrate that system error rates 1.6% [1.0%], mean [standard deviation], at heel contact and 0.5% [0.2%] at toe off. the results of this study are encouraging and provide another step towards a clinically viable lower limb intent recognition system for a powered knee-ankle prosthesis.

关键词： Legged locomotion Prosthetics Steady-state Knee Mechanical sensors Performance evaluation pattern recognition

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Understanding behavioral differences between short and long-term drinking abstainers from social media 12th

Understanding behavioral differences between short and long-...

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12th international conference on Advanced Data Mining and Applications, ADMA 2016

作者： Harikumar, Haripriya Nguyen, thin Gupta, Sunil Rana, Santu Kaimal, Ramachandra Venkatesh, Svetha Centre for Pattern Recognition and Data Analytics Deakin University Geelong Australia Computer Science and Engineering Department Amrita University Kollam India

ISBN: (纸本)9783319495859

Drinking alcohol has high cost on society. the journey from being a regular drinker to a successful quitter may be a long and hard journey, fraught with the risk to relapse. Research has shown that certain behavioral changes can be effective towards staying abstained. Traditional way to conduct research on drinking abstainers uses questionnaire based approach to collect data from a curated group of people. However, it is an expensive approach in both cost and time and often results in small data with less diversity. Recently, social media has emerged as a rich data source. Reddit is one such social media platform that has a community (‘subreddit’) with an interest to quit drinking. the discussions among the group dates back to year 2011 and contain more than 40,000 posts. this large scale data is generated by users themselves and without being limited by any survey questionnaires. the most predictive factors from the features (unigrams, topics and LIWC) associated with short-term and long-term abstinence are identified using Lasso. It is seen that many common patterns manifest in unigrams, topics and LIWC. Whilst topics provided much richer associations between a group of words and the outcome, unigrams and LIWC are found to be good at finding highly predictive solo and psycho linguistically important words. Combining them we have found that many interesting patterns that are associated with the successful attempt made by the long-term abstainer, at the same time finding many of the common issues faced during the initial period of abstinence. © Springer international Publishing AG 2016.

关键词： Surveys

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Experimental analysis of the relationship between neural and muscular recordings during hand control

Experimental analysis of the relationship between neural and...

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IEEE/RAS-EMBS international conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Emiliano Noce Loredana Zollo Angelo Davalli Rinaldo Sacchetti Eugenio Guglielmelli Unit of Biomedical Robotics and Biomicrosystems Universita Campus Biomedico di Roma Rome Italy INAIL Centro Protesi Bologna Italy

ISBN: (纸本)9781509032884

In this study, the relationship between the electromyographic (EMG) and neural signals (ENG) recorded during hand control is investigated. EMG and ENG signals are both recorded from an amputee during the ENG control of a hand prosthesis. the EMG signal was processed with standard techniques to compute the envelope. For the neural signal, the processing involved the evaluation of the energy of the recordings with a moving average and the best combination of window width and multiplier for the standard deviation was searched for. Hence, a new curve for the neural signal was generated, gathering information about amplitude and occurrence of action potentials during the motion task. Its correlation with the EMG envelope was studied by means of a parameter purposely conceived, which accounts for the ratio between the areas under the two curves. the proposed approach has been applied to little finger flexion and open hand tasks. Ten movements for each task have been processed for the aim of this study and a comparative analysis with the Pearson coefficient has been carried out.

关键词： Electromyography Standards Electrodes Prosthetics Muscles pattern recognition Robot sensing systems

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Comparison of Different Learning Algorithms for pattern recognition with Hopfield's Neural Network 6th

Comparison of Different Learning Algorithms for Pattern Reco...

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6th Annual international conference on Biologically Inspired Cognitive Architectures (BICA)

作者： Szandala, Tomasz Wroclaw Univ Technol PL-50370 Wroclaw Poland

Hopfield neural networks can be used for compression, approximation, steering. But they are most commonly used for pattern recognition thanks to their associative memory trait. In order to fulfill this task, the network has to be trained with one of algorithms. In this paper I will try to implement three of the most popular ones and compare their effectiveness by trying to recognize various patterns consisting of binary input arrays. the tests will use Hebbian learning, Oja's Hebbian modification and pseudo-inverse, which proves to be most promising training algorithm.

关键词： hopfield machine learning pattern recognition hebbian oja pseudoinverse

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Consensus-based prediction of RNA and DNA binding residues from protein sequences 6th

Consensus-based prediction of RNA and DNA binding residues f...

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6th international conference on pattern recognition and Machine Intelligence, PReMI 2015

作者： Yan, Jing Kurgan, Lukasz Electrical and Computer Engineering University of Alberta EdmontonT6G 2V4 Canada

Computational prediction of RNA- and DNA-binding residues from protein sequences offers a high-throughput and accurate solution to functionally annotate the avalanche of the protein sequence data. Although many predictors exist, the efforts to improve predictive performance with the use of consensus methods are so far limited. We explore and empirically compare a comprehensive set of different designs of consensuses including simple approaches that combine binary predictions and more sophisticated machine learning models. We consider both DNA- and RNA-binding motivated by similarities in these interactions, which should lead to similar conclusions. We observe that the simple consensuses do not provide improved predictive performance when applied to sequences that share low similarity with the datasets used to build their input predictors. However, use of machine learning models, such as linear regression, Support Vector Machine and Naïve Bayes, results in improved predictive performance when compared with the best individual predictors for the prediction of DNA- and RNA-binding residues. © Springer international Publishing Switzerland 2015.

关键词： Forecasting

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A new post-processing method to detect brain tumor using rough-fuzzy clustering 6th

A new post-processing method to detect brain tumor using rou...

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6th international conference on pattern recognition and Machine Intelligence, PReMI 2015

作者： Roy, Shaswati Maji, Pradipta Biomedical Imaging and Bioinformatics Lab Machine Intelligence Unit Indian Statistical Institute Kolkata India

Automatic and accurate brain tumor segmentation from MR images is one of the important problems in cancer research. However, the lack of shape prior and weak contrast at boundary make unsupervised brain tumor segmentation more challenging. In this background, a new brain tumor segmentation method is being developed, integrating judiciously the merits of multiresolution image analysis technique and rough-fuzzy clustering. One of the major issues of the clustering based segmentation method is how to extract brain tumor accurately, since tumors may not have clearly defined intensity or textural boundaries. In this regard, this paper presents a new post-processing method for clustering based brain tumor detection. It combines the merits of mathematical morphology and the concept of rough set based region growing approach to refine the result obtained after clustering, thereby ensuring the accurateness of brain tumor segmentation application. the performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images. © Springer international Publishing Switzerland 2015.

关键词： Mathematical morphology

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Report on the first contest on graph matching algorithms for pattern search in biological databases 10

Report on the first contest on graph matching algorithms for...

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10th iapr-TC-15 international Workshop on Graph-Based Representations in pattern recognition, GbRPR 2015

作者： Carletti, Vincenzo Foggia, Pasquale Vento, Mario Jiang, Xiaoyi Department of Information Engineering Electrical Engineering and Applied Mathematics University of Salerno Fisciano Italy Department of Computer Science University of Münster Münster Germany

ISBN: (纸本)9783319182230

Graphs are a powerful data structure that can be applied to several problems in bioinformatics, and efficient graph matching is often a tool required for several applications that try to extract useful information from large databases of graphs. While graph matching is in general a NP-complete problem, several algorithms exist that can be fast enough on practical graphs. However, there is no single algorithm that is able to outperform the others on every kind of graphs, and so it is of paramount importance to assess the algorithms on graphs coming from the actual problem domain. To this aim, we have organized the first edition of the Contest on Graph Matching Algorithms for pattern Search in Biological Databases, hosted by the ICPR2014 conference, so as to provide an opportunity for comparing state-of-the-art matching algorithms on a new graph database built using several kinds of real-world graphs found in bioinformatics applications. the participating algorithms were evaluated with respect to both their computation time and their memory usage. this paper will describe the contest task and databases, will provide a brief outline of the participating algorithms, and will present the results of the contest. © Springer international Publishing Switzerland 2015.

关键词： bioinformatics

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