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检索条件"任意字段=3rd IAPR International Conference on Pattern Recognition in Bioinformatics"

共 2194 条记录，以下是481-490 订阅

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Joint iapr international Workshops on Structural and Syntactic pattern recognition, SSPR 2018 and Statistical Techniques in pattern recognition, SPR 2018

Joint IAPR International Workshops on Structural and Syntact...

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Joint iapr international Workshops on Structural and Syntactic pattern recognition, SSPR 2018 and Statistical Techniques in pattern recognition, SPR 2018

ISBN: (纸本)9783319977843

The proceedings contain 49 papers. The special focus in this conference is on Structural and Syntactic pattern recognition. The topics include: Learning deep embeddings via margin-based discriminate loss;protein remote homology detection using dissimilarity-based multiple instance learning;local binary patterns based on subspace representation of image patch for face recognition;an image-based representation for graph classification;visual tracking via patch-based absorbing markov chain;gradient descent for gaussian processes variance reduction;sparsification of indefinite learning models;semi-supervised clustering framework based on active learning for real data;supervised classification using feature space partitioning;malignant brain tumor classification using the random forest method;deep homography estimation with pairwise invertibility constraint;graph time series analysis using transfer entropy;analyzing time series from chinese financial market using a linear-time graph kernel;a preliminary survey of analyzing dynamic time-varying financial networks using graph kernels;few-example affine invariant ear detection in the wild;line voronoi diagrams using elliptical distances;modelling the generalised median correspondence through an edit distance;learning the sub-optimal graph edit distance edit costs based on an embedded model;ring based approximation of graph edit distance;graph edit distance in the exact context;rotationally invariant bark recognition;The VF3-light subgraph isomorphism algorithm: When doing less is more effective;a deep neural network architecture to estimate node assignment costs for the graph edit distance;error-tolerant geometric graph similarity;learning cost functions for graph matching;matrix regression-based classification for face recognition;plenoptic imaging for seeing through turbulence;weighted local mutual information for 2D-3D registration in vascular interventions.

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Towards Better Soft-Tissue Segmentation Based on Gestalt Psychology 3

Towards Better Soft-Tissue Segmentation Based on Gestalt Psy...

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3rd IEEE international conference on Image, Vision and Computing (ICIVC)

作者： Bo, Qirong Feng, Jun Li, Pan Lv, Zhaohui Zhang, Jing Northwest Univ Inst Informat Sci & Technol Xian Shaanxi Peoples R China Lamar Univ Comp Sci Dept Beaumont TX 77710 USA

ISBN: (纸本)9781538649916

According to gestalt psychology theory, the human brain merges and simplifies unrelated units by some relations through eyes for subsequent cognition. We introduce a new segmentation framework based on gestalt psychology in this paper. An input image is first divided into visual patches using two gestalt principles, similarity and proximity, by a clustering method, and then the visual patches are grouped to form soft tissues by a classification step using the spatial relationship and texture features. We evaluated the proposed method using TCIA database at both sectional level and volumetric level. The experimental results demonstrated the efficiency and robustness of the presented method and indicated its promising applications in the field of medical image processing.

关键词： abdominal CT image soft tiusse segmentation visual patch pattern recognition

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Scene Text Detection Based on Enhanced Multi-channels MSER and a Fast Text Grouping Process 3

Scene Text Detection Based on Enhanced Multi-channels MSER a...

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3rd IEEE international conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Dai, Jin Wang, Zu Zhao, Xianjing Shao, Shuai Chongqing Univ Posts & Telecommun Sch Software Engn Chongqing Peoples R China

ISBN: (纸本)9781538643013

Scene text detection has become a popular research in computer vision and pattern recognition field in recent years because of the accurate and rich information carried by scene text. Now component-based methods have become the trend, and the detection result is largely determined by the success of filtering text-like non-text regions. The main task of this paper is to reduce the time complexity without a big fall in recall. First an enhanced multi-channels MSER model is introduced: Before extracting MSER, the image is sharpened by using the Laplacian and Gaussian blur and multi-channels is utilized, then the step of the threshold used in MSER algorithm is set to the minimum in order to get more refined MSERs. Second, two novel scene text features local contrast and boundary key points are proposed to better distinguish text regions from non-text regions. Finally, a fast text grouping algorithm is achieved which reduce the time complexity. Experiments on both ICDAR 2011 and ICDAR 2013 show that the recall of the proposed method is improved by 3%.

关键词： MSER multi-channels scene text text detection

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Proceedings of the 3rd international conference on Informatics and Computing, ICIC 2018

Proceedings of the 3rd International Conference on Informati...

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3rd international conference on Informatics and Computing, ICIC 2018

ISBN: (纸本)9781538669204

The proceedings contain 140 papers. The topics discussed include: implementation of green IT In education industries;multi-facet analysis of technology-enhanced learning;batik pattern identification using GLCM and artificial neural network backpropagation;SPOT: a low cost intelligent parking system for urban malls;application development based on mobile learning framework on rice and vegetable agriculture;a collaborative process scheme in strategic information systems planning;android-based text recognition on receipt bill for tax sampling system;automatic time-based learning type analysis towards dynamic personalization;the physical and engineering requirements of scalable, decentralized, distributed, large-scale MIMO;design of orchid monitoring system based on IoT;and influence of blended learning on learning result of algorithm and programming.

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Music Instrument Identification Based on a 2-D Representation 3

Music Instrument Identification Based on a 2-D Representatio...

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3rd international conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (IGEECCOT)

作者： Ghosh, Alekhya Pal, Arghadeep Sil, Dibakar Palit, Sarbani Univ Calcutta IRPEL Elect & Commun Engn Kolkata India Natl Inst Technol Elect & Commun Engn Durgapur India Indian Stat Inst Comp Vis & Pattern Recognit Unit Kolkata India

ISBN: (纸本)9781538651308

Automatic recognition of musical instruments has been a great problem in the field of digital signal processing. In this work a novel, compact set of features obtained by transforming a music signal to the spatial domain is introduced with promising results. Preliminary results on a popular music database, presented in terms of precision, recall and identification accuracy, are highly encouraging. The best result comprises an accuracy of 84.02% by Decision Tree (DT) for a set of 9 instruments belonging to different families. The accuracy for predicting the instrument family 96.07% for string family and for wind instrument the overall prediction accuracy is 90.78%. Further inclusion of some other features from some available works are also checked leading to slight increase in the accuracy. The obtained results are also compared with the result predicted by the VGG - 16 network on the same dataset. The feature set containing 8 features that introduces less computational complexity compared to available works, may be considered as a major contribution. The comparison shows, we can replicate nearly accurate classification through our proposed method in less amount of time than deep neural architecture.

关键词： music instrument recognition spatial features random forest decision tree

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3D hand gesture recognition by analysing set-of-joints trajectories 2nd

3D hand gesture recognition by analysing set-of-joints traje...

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2nd international Workshop on Understanding Human Activities Through 3D Sensors, UHA3DS 2016 Held in Conjunction with the 23rd international conference on pattern recognition, ICPR 2016

作者： De Smedt, Quentin Wannous, Hazem Vandeborre, Jean-Philippe Télécom Lille CNRS UMR 9189 - Cristal Lille59000 France Télécom Lille Univ. Lille CNRS UMR 9189 - Cristal Lille59000 France

ISBN: (纸本)9783319918624

Hand gesture recognition is recently becoming one of the most attractive field of research in pattern recognition. In this paper, a skeleton-based approach is proposed for 3D hand gesture recognition. Specifically, we consider the sequential data of hand geometric configuration to capture the hand shape variation, and explore the temporal character of hand motion. 3D Hand gesture are represented as a set of relevant spatiotemporal motion trajectories of hand-parts in an Euclidean space. Trajectories are then interpreted as elements lying on Riemannian manifold of shape space to capture their shape variations and achieve gesture recognition using a linear SVM classifier. The proposed approach is evaluated on a challenging hand gesture dataset containing 14 gestures, performed by 20 participants performing the same gesture with two different numbers of fingers. Experimental results show that our skeleton-based approach consistently achieves superior performance over a depth-based approach. © 2018, Springer international Publishing AG, part of Springer Nature.

关键词： Gesture recognition

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COMPLEXIS 2018 - Proceedings of the 3rd international conference on Complexity, Future Information Systems and Risk

COMPLEXIS 2018 - Proceedings of the 3rd International Confer...

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3rd international conference on Complexity, Future Information Systems and Risk, COMPLEXIS 2018

ISBN: (纸本)9789897582974

The proceedings contain 19 papers. The topics discussed include: communicability in networked systems - implications for stability, spatial efficiency and dynamical process;why so emotional? an analysis of emotional Bot-generated Content on Twitter;PaaS-BDP a multi-cloud architectural pattern for big data processing on a platform-as-a-service model;a new pricing model for freelancing platforms based on financial and social capital;on code-prompting auto-catalytic sets and the origins of coded life;using tag based semantic annotation to empower client and REST service interaction;a novel algorithm for bi-level image coding and lossless compression based on virtual ant colonies;proposing a holistic framework for the assessment and management of manufacturing complexity through data-centric and human-centric approaches;CBR-mining approach to improve learning system engineering in a collaborative e-learning platform;a new pricing model for freelancing platforms based on financial and social capital;on the public perception of police forces in riot events - the role of emotions in three major social networks during the 2017 G20 riots;complexity evaluation with business process modeling and simulation;modeling and implementation of a Ludic application using simple reactive agents - hydrological impact of high Andean ecosystems;bio-backfill: a scheduling policy enhancing the performance of bioinformatics workflows in shared clusters;and the fuzzy mortality model based on quaternion theory.

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Hardware based artificial neural networks for basic pattern recognition application 3

Hardware based artificial neural networks for basic pattern ...

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3rd international conference on Informatics and Computing, ICIC 2018

作者： Sudiro, Sunny Arief Wardijono, Bheta Agus Arianto, Adi Putra Widianti, Linda Wahyu Wardhani, Ire Puspa STMIK Jakarta STI and K Jakarta Indonesia Computer Science Departement STMIK Jakarta STI and K Jakarta Indonesia Electrical Engineering Department Gunadarma University Jakarta Indonesia Information System Departement STMIK Jakarta STI and K Jakarta Indonesia

ISBN: (纸本)9781538669204

Nowadays, rapidly evolved image processing technology has negative effect. Criminals often use image processing technology to manipulate important data based on the image, such as bio data, signature, and stamp. Some anti-manipulate method is needed to reduce the further effect. A combination of computer vision and an artificial neural network can be used to build an application to be as anti-manipulate image method. This article proposed an approach by developing an application that can recognize the image pattern using K-Nearest Neighbor algorithm and calculate Euclidean distance between image features vector. Application use Sobel edge detection (3x3 matrix convolution) to obtain image features vector. Application use CogniStixTM as an artificial neural network hardware and CogniSoft SDK Express as a CogniStixTM driver. Application is released in three version, which is v1.0 with RoI size =24. Vl.1 with RoI size= image resolution, and v1.2 with RoI size =96. From the evaluation result, the best version is application version 1.1, which have accuracy rate of 100% (or approximately 100% in long term sample). All application version has a drawback, they not robust with deformation of input pattern. The application can be developed further to be integrated with FPGA board for more advanced image recognition in embedded system. © 2018 IEEE.

关键词： Neural networks

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3rd international conference on High Performance Computing in Science and Engineering, HPCSE 2017

3rd International Conference on High Performance Computing i...

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3rd international conference on High Performance Computing in Science and Engineering, HPCSE 2017

ISBN: (纸本)9783319971353

The proceedings contain 15 papers. The special focus in this conference is on High Performance Computing in Science and Engineering. The topics include: MERIC and RADAR generator: Tools for energy evaluation and runtime tuning of HPC applications;Disc vs. annulus: On the bleaching pattern optimization for FRAP experiments;modeling and simulation of microalgae growth in a Couette-Taylor bioreactor;karhunen-Loéve decomposition of isotropic Gaussian random fields using a tensor approximation of autocovariance kernel;a Bayesian approach to the identification problem with given material interfaces in the darcy flow;applications of trace estimation techniques;fourier method for approximating eigenvalues of indefinite stekloff operator;proportionality-based gradient methods with applications in contact mechanics;Schur complement-schwarz DD preconditioners for non-stationary darcy flow problems;relating computed and exact entities in methods based on lanczos tridiagonalization;software tool for cranial orthosis design;Implementation of BM3D filter on intel xeon phi for rendering in blender cycles;Investigating convergence of linear SVM implemented in PermonSVM employing MPRGP algorithm.

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Review of texture descriptors for texture classification 3rd

Review of texture descriptors for texture classification

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3rd international conference on Computer and Communication Technologies, IC3T 2016

作者： Simon, Philomina Uma, V. Department of Computer Science University of Kerala Thiruvananthapuram India Department of Computer Science Pondicherry University Pondicherry India

ISBN: (纸本)9789811032226

Texture classification is a process of distinguishing or classifying different textures into separate classes. Finding an efficient texture descriptor is a vital step for performing accurate texture classification. The research area of texture classification is widely investigated in several computer vision and pattern recognition problems. In this paper, texture descriptors applied for the texture classification in the literature are summarized. A general framework for texture classification and significance of texture descriptors are also presented in this paper. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Local binary pattern

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