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1st Mediterranean conference on pattern recognition and Artificial Intelligence, MedPRAI 2016

作者： Meraoumia, Abdallah Laimeche, Lakhdar Bendjenna, Hakim Chitroub, Salim University of Larbi Tebessi Tebessa Algeria Electronics and Computer Science Faculty USTHB Algiers Algeria

ISBN: (纸本)9781450348768

A biometric technology is an emerging field of information technology which can be used to identifying identity of unknown individual based on some characteristics derived from specific physiological and/or behavioral characteristics that the individual possesses. Thus, among several biometric characteristics, which can be derived from the hand, palmprint has been effectively used to improve identification for last years. So far, majority of research works on this biometric trait are fundamentally based on a gray-scale image which acquired using a visible light. Recently, multispectral imaging technology has been used to make the biometric system more efficient. In this work, in order to increase the discriminating ability and the classification system accuracy, we propose a multimodal system which each spectral band of palmprint operates separately and their results are fused at matching score level. In our study, each spectral band is represented by features extracted by PCANet deep learning technique. The proposed scheme is validated using the available CASIA multispectral palmprint database of 100 users. The obtained results showed that the proposed method is very efficient, which can be improved the accuracy rate. © 2016 ACM.

关键词： Biometrics

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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1st Mediterranean conference on pattern recognition and Artificial Intelligence, MedPRAI 2016

ISBN: (纸本)9781450348768

The proceedings contain 24 papers. The topics discussed include: polarimetric SAR images classification and texture features;a new approach to improve the success and solving the UGVs cooperation for SLAM problem, using a SVSF filter;a novel social networks approach based on QoS for web services selection;segmentation by tangent filter;a robust approach for mammographic image classification using NSVC algorithm;a novel heuristic based simulated annealing for the capacitated location routing problem;a comparative study of metaheuristics for liver disorders prediction;a hybrid stochastic HS-GRASP algorithm for the VRP with time windows;aggregation as a simple seed for collective decision;improving kernel so subspace clustering algorithms using a particle swarm optimization;hidden Markov random field model and BFGS algorithm for brain image segmentation;fast soft shadow with screen space ambient occlusion for real time rendering;application of pixel selection in pixel-based classification for automatic white blood cell segmentation;do we have to trust the deep learning methods for palmprints identification?;extraction of road networks from the VHSR satellite images by the algorithm F;and improving kernel so subspace clustering algorithms using a particle swarm optimization.

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India international conference on Information processing, IICIP 2016 - Proceedings

India International Conference on Information Processing, II...

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1st India international conference on Information processing, IICIP 2016

ISBN: (纸本)9781467369848

The proceedings contain 99 papers. The topics discussed include: implementation of improved fractional order capacitor approximations in analog circuits;eye-blink rate detection for fatigue determination;an un-supervised image segmentation technique based on multi-objective gravitational search algorithm (MOGSA);measurement of bifurcation features in retinal fundus images;class/ aspect level mutation operators in aspect-oriented software systems;a hybrid approach for test case prioritization and optimization using meta-heuristics techniques;prioritization of code restructuring for severely affected classes under release time constraints;dual segment video watermarking using energy efficient technique;improving lifetime of wireless sensor networks by mitigating correlated data using LEACH protocol;improved and distributive code assignment technique for interference-free CDMA network;an analysis of machine learning techniques (J48 & Adaboost) for classification;an approach for regression test case selection and prioritization for object oriented software for obfuscated code;speed control of hybrid electric vehicle using PSO based fractional order PID controller;and neuro-fuzzy based approach to event driven software testing: a new opportunity.

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A new software collection for 3D processing of X-ray CT images 1st

A new software collection for 3D processing of X-ray CT imag...

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1st international conference on Energy Geotechnics (ICEGT)

作者： Chauhan, S. Ruehaak, W. Sass, I Anbergen, H. Kabdenov, A. Freise, M. Wille, T. Tech Univ Darmstadt Inst Angew Geowissensch Fachgebiet Angew Geotherm Darmstadt Germany APS Antriebs Pruf & Steuerteckn GmbH Rosdorf Germany

ISBN: (纸本)9781315315249;9781138032996

The identification of accurately segmented phases in images observed through X-ray microcomputer tomography (XCT) is vital towards characterizing uncertainties involved in determining the geometries of pore network. Currently popular methods such as histogram, thresholding which are commonly used for XCT image segmentation exhibit a number of shortfalls. In this paper a new software is proposed, which is based on machine learning (ML) techniques, for the 2D/3D visualization of XCT data. The segmentation and classification of different phases are based on feature vector selection. Hence relative porosities and trends in pore size distribution can be computed. In this study, the computational performance is optimised using correlation-based feature vector selection, demonstrated using unsupervised, supervised and ensemble ML techniques. Furthermore, accuracies of ML techniques are accessed based on entropy, purity, and receiver operation characteristics.

关键词： image segmentation

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An investigation of machine learning and neural computation paradigms in the design of clinical decision support systems (CDSSs) 1

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8th international conference on Brain Inspired Cognitive Systems, BICS 2016

作者： Wajid, Summrina K. Hussain, Amir Luo, Bin Huang, Kaizhu Computing Science and Mathematics School of Natural Sciences University of Stirling Stirling United Kingdom School of Computing Science and Technology Anhui University Hefei China Xi’an Jiaotong-Liverpool University Suzhou China

ISBN: (数字)9783319496856

ISBN: (纸本)9783319496849

This paper reviews the state of the art techniques for designing next generation CDSSs. CDSS can aid physicians and radiologists to better analyse and treat patients by combining their respective clinical expertise with complementary capabilities of the computers. CDSSs comprise many techniques from inter-desciplinary fields of medical image acquisition, image processing and pattern recognition, neural perception and pattern classifiers for medical data organization, and finally, analysis and optimization to enhance overall system performance. This paper discusses some of the current challenges in designing an efficient CDSS as well as some of the latest techniques that have been proposed to meet these challenges, primarily, by finding informative patterns in the medical dataset, analysing them and building a descriptive model of the object of interest, thus aiding in enhanced medical diagnosis. © Springer international Publishing AG 2016.

关键词： Decision support systems

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A 1 TOPS/W Analog Deep machine-learning Engine With Floating-Gate storage in 0.13 μm CMOS

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IEEE JOURNAL OF SOLID-stATE CIRCUITS 2015年第1期50卷 270-281页

作者： Lu, Junjie Young, steven Arel, Itamar Holleman, Jeremy Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

An analog implementation of a deep machine-learning system for efficient feature extraction is presented in this work. It features online unsupervised trainability and non-volatile floating-gate analog storage. It utilizes a massively parallel reconfigurable current-mode analog architecture to realize efficient computation, and leverages algorithm-level feedback to provide robustness to circuit imperfections in analog signal processing. A 3-layer, 7-node analog deep machine-learning engine was fabricated in a 0.13 mu m standard CMOS process, occupying 0.36 mm(2) active area. At a processing speed of 8300 input vectors per second, it consumes 11.4 mu W from the 3 V supply, achieving 1x10(12) operation per second per Watt of peak energy efficiency. Measurement demonstrates real-time cluster analysis, and feature extraction for pattern recognition with 8-fold dimension reduction with an accuracy comparable to the floating-point software simulation baseline.

关键词： Analog signal processing current mode arithmetic deep machine learning floating gate neuromorphic engineering translinear circuits

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Jewelry stones Classification: Case study 7

Jewelry Stones Classification: Case Study

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7th international conference of Soft Computing and pattern recognition (SoCPaR)

作者： Hurtik, Petr Vajgl, Marek Burda, Michal Univ Ostrava Ctr Excellence IT4Innovat Inst Res & Applicat Fuzzy Modeling 30 Dubna 22 CZ-70103 Ostrava 1 Czech Republic

ISBN: (纸本)9781467393607

The paper introduces a real-life industrial problem: a jewelry stones classification. The stones are represented by their camera images. The goal of the contract was to evaluate stones into two (or more) specified classes according to their quality. Given requirements include very high processing speed and success rate of the classification. The goal of this paper is to publish a report of this contract and show a way how this task can be solved. In this paper we aim to usage of machine learning with respect to the image processing. We also design own learning and classification algorithm and answer the question if there is a place for a new machine learning algorithm. As an output of this paper a benchmark of the proposed algorithm with 81 state-of-the-art machine learning methods is presented.

关键词： image classification machine learning image processing perceptron separation tree

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Blind path obstacle detector using smartphone camera and line laser emitter

Blind path obstacle detector using smartphone camera and lin...

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international conference on Technology and Innovation in Sports, Health and Wellbeing (TISHW)

作者： Rimon Saffoury Peter Blank Julian Sessner Benjamin H. Groh Christine F. Martindale Eva Dorschky Joerg Franke Bjoern M. Eskofier Digital Sports Group Pattern Recognition Lab Department of Computer Science Institute for Factory Automation and Production Systems Friedrich-Alexander University Erlangen-Numberg (FAU) Erlangen Germany

ISBN: (纸本)9781509057283

Visually impaired people find navigating within unfamiliar environments challenging. Many smart systems have been proposed to help blind people in these difficult, often dangerous, situations. However, some of them are uncomfortable, difficult to obtain or simply too expensive. In this paper, a low-cost wearable system for visually impaired people was implemented which allows them to detect and locate obstacles in their locality. The proposed system consists of two main hardware components, a laser pointer ($12) and an android smart phone, making our system relatively cheap and accessible. The collision avoidance algorithm uses image processing to measure distances to objects in the environment. This is based on laser light triangulation. This obstacle detection is enhanced by edge detection within the captured image. An additional feature of the system is to recognize and warn the user when stairs are present in the camera's field of view. Obstacles are brought to the user's attention using an acoustic signal. Our system was shown to be robust, with only 5 % false alarm rate and a sensitivity of 90 % for 1 cm wide obstacles.

关键词： Measurement by laser beam Laser feedback Cameras Lasers Smart phones Navigation

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FAst HAND DETECTION AND GEstURE recognition 14

FAST HAND DETECTION AND GESTURE RECOGNITION

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international conference on machine learning and Cybernetics (ICMLC)

作者： Wang, Yuh-Rau Syu, Jia-Liang Li, Hsin-Ting Yang, Ling St Johns Univ Dept Comp Sci & Informat Engn Taipei Taiwan Tamkang Univ Dept Elect Engn Taipei Taiwan St Johns Univ Dept Mkt & Logist Management Taipei Taiwan

ISBN: (纸本)9781467372206

A fast hand detection and gesture recognition method is proposed in this paper. To reduce the computation time, we employ symmetric mask-based discrete wavelet transform (SMDWT) to reduce the image resolution and then utilize the extracted characteristics to perform hand detection and gesture recognition. The proposed method reduces about 66% of the overall computation time. Experimental results show that the proposed real time hand detection and gesture recognition methods can detect fast and accurately, and can be implemented on embedded system easily. The average gesture recognition rate is around 97.5%.

关键词： Discrete wavelet transform Hand detection Skin color detection Gesture recognition

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Odia Braille: Text Transcription via image processing 1

Odia Braille: Text Transcription via Image Processing

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international conference On Futuristic Trends in Computational Analysis and Knowledge Management

作者： Parvathi, K. Samal, Bijet Maynoher Das, Jitendra Kumar KIIT Univ Sch Elect Engn Bhubaneswar Odisha India

ISBN: (纸本)9781479984336

Braille-a model introduced to reduce the illiteracy rate among the visually challenged people. There has been a lot of scope for the conversion of English language to Braille but, the problem arises when the masses are unable to understand the communication by the visually challenged people. This paper focuses on the conversion of the Braille code representing Odia language(a language widely spoken in East India) into Odia word as text. For this, image processing using MATLAB technique provides a suitable platform to perform the segmentation of Braille cell for pattern selection and hence, Odia letter and word recognition. Braille Data Base creation acts as a storage system for the process and its accuracy is also tested which is explained in this paper.

关键词： visually challenged image processing image segmentation Braille Data Base Odia braille pattern recognition Histogram

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