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3rd international conference on Artificial Intelligence, Modelling and Simulation (AIMS)

作者： De Guzman, Launcelot C. Maglaque, Ryan Paolo C. Torres, Vianca May B. Zapido, Simon Philippe A. Cordel, Macario O., II De La Salle Univ Ctr Automat Res Coll Comp Studies Manila Philippines

ISBN: (纸本)9781467386753

There are several current systems developed to identify common skin lesions such as eczema that utilize image processing and most of these apply feature extraction techniques and machine learning algorithms. These systems extract the features from pre-processed images and use them for identifying the skin lesions through machine learning as the core. This paper presents the design and evaluation of a system that implements a multi-model, multi-level system using the Artificial Neural Network (ANN) architecture for eczema detection. In this work, multi-model system is defined as architecture with different models depending on the input characteristic. The outputs of these models are integrated by a decision layer, thus multi-level, which computes the probability of an eczema case. The resulting system has 68.37% average confidence level as opposed to the 63.01% of the single level, i.e. single model, system in the actual testing of eczema versus non-eczema cases. Furthermore, the multi-model, multi-level design produces more stable models in the training phase wherein overfitting was reduced.

关键词： Computer-assisted diagnosis pattern recognition skin lesion detection Artificial Neural Network multi-model multi-level systems

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3rd iapr international conference on pattern recognition in bioinformatics, PRIB 2008, Proceedings

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3rd iapr international conference on pattern recognition in bioinformatics, PRIB 2008

ISBN: (纸本)3540884343

The proceedings contain 39 papers. The topics discussed include: sequence based prediction of protein mutant stability and discrimination of thermophilic proteins;a method to find sequentially separated motifsin biological sequences (SSMBS);DFS based partial pathways in GA for protein structure prediction;evaluation of the stability of folding nucleus upon mutation;prediction of protein beta-sheets: dynamic programming versus grammatical approach;using multi-scale glide zoom window feature extraction approach to predict protein homo-oligomer types;extraction of binding sites in proteins by searching for similar local molecular surfaces;a clustering based hybrid system for mass spectrometry data analysis;a modified Markov clustering approach for protein sequence clustering;and domain-domain interaction identification with a feature selection approach.

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DCT trigger for a detection of very inclined showers in the Pierre Auger surface detector Engineering Array in the new High-Resolution Front-End based on the Cyclone V FPGA

DCT trigger for a detection of very inclined showers in the ...

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3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Szadkowski, Zbigniew Univ Lodz Dept Phys & Appl Informat Fac High Energy Astrophys Pomorska 149 PL-90236 Lodz Poland

ISBN: (纸本)9788360810668

The paper presents the first results from the trigger based on the Discrete Cosine Transform (DCT) operating in the new Front-End Boards with Cyclone V FPGA deployed in 8 test surface detectors in the Pierre Auger Engineering Array. The patterns of the Analog-to-Digial Converter (ADC) traces generated by very inclined showers were obtained from the Auger database and from the CORSIKA simulation package supported next by OffLine reconstruction Auger platform which gives a predicted digitized signal profiles. Simulations for many variants of the initial angle of shower, initialization depth in the atmosphere, type of particle and its initial energy gave a boundary of the DCT coefficients used next for the on-line pattern recognition in the FPGA. Preliminary results have proven a right approach. We registered several showers triggered by the DCT for 120 MSps and 160 MSps.

关键词： cosmic ray apparatus cosmic ray showers Analog-to-Digial Converter trace patterns Auger database CORSIKA simulation package Cyclone V FPGA DCT coefficients DCT trigger Discrete Cosine Transform Front-End Boards OffLine reconstruction Auger platform Pierre Auger surface detector digitized signal profiles on-line pattern recognition shower initial angle variants very inclined shower detection Arrays Attenuation Cyclones Detectors Discrete cosine transforms Field programmable gate arrays Standards discrete cosine transforms Field programmable gate arrays cosmic ray showers cyclones detector arrays Attenuation Attenuation DCT gene front-ends Spiral wood bits

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Automatic Classification of Fruit Defects based on Co-Occurrence Matrix and Neural Networks

Automatic Classification of Fruit Defects based on Co-Occurr...

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3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Capizzi, Giacomo Lo Sciuto, Grazia Napoli, Christian Tramontana, Emiliano Wozniak, Marcin Univ Catania Dept Elect & Informat Engn Viale A Doria 6 I-95125 Catania Italy Univ Rome Tre Dept Elect Engn I-00146 Rome Italy Univ Catania Dept Math & Informat I-95125 Catania Italy Silesian Tech Univ Inst Math PL-44100 Gliwice Poland

ISBN: (纸本)9788360810668

Nowadays the effective and fast detection of fruit defects is one of the main concerns for fruit selling companies. This paper presents a new approach that classifies fruit surface defects in color and texture using Radial Basis Probabilistic Neural Networks (RBPNN). The texture and gray features of defect area are extracted by computing a gray level co-occurrence matrix and then defect areas are classified by the applied RBPNN solution.

关键词： Co-occurrence Matrix Texture Analysis pattern recognition Probabilistic Neural Network

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Guest Editorial: pattern recognition in bioinformatics

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND bioinformatics 2014年第3期11卷 498-499页

作者： Marchiori, Elena Ngom, Alioune Acharya, Raj Radboud Univ Nijmegen Fac Sci Dept Comp Sci NL-6525 AJ Nijmegen Netherlands Univ Windsor Sch Comp Sci Windsor ON N9B 3P4 Canada Penn State Univ Coll Engn Dept Comp Sci & Engn University Pk PA 16802 USA

Development and application of pattern recognition techniques in the field of bioinformatics is of utmost importance for gaining new insights about phenomena in life sciences through the analysis of biological data. In this special section, three research manuscripts in their significantly extended form were selected from the papers presented at the Eighth iapr international conference on pattern recognition in bioinformatics (PRIB 2013), which was held in Nice, France.

关键词： Special Issues And Sections Meetings bioinformatics Genomics pattern recognition Feature Extraction Semantics Proteins

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Freehand push-gesture recognition via 3D palm trajectory modeling 3

Freehand push-gesture recognition via 3D palm trajectory mod...

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3rd international Symposium of Chinese CHI, Chinese CHI 2015

作者： Lin, Shih-Yao Shie, Chuen-Kai Chen, Chu-Song Hung, Yi-Ping Graduate Institute of Networking and Multimedia National Taiwan University Taipei Taiwan Institute of Information Science Academia Sinica Taipei Taiwan

ISBN: (纸本)9781450334648

This paper aims at improving the recognition of 3D push-hand gesture, which can trigger a target selection command with our hands in the air. Although general 3D push-gesture ecognizers have been developed and widely used for this purpose, a severe weakness of the current push-recognizers is that they are instable to askew-pushing problems that happen frequently in practice. It is because that the push trajectory of our hand is not always a straightforward movement due to the anatomy of human, but would vary depending on the location of the target relative to the users. We explore the 3D palm trajectories of push-gestures in different locations around the user, and propose a 3D push-gesture modeling approach by learning 3D palm trajectories to solve the askew-click problem. We evaluate the proposed recognizers on a click-gesture dataset, and compare it with the prior arts of forward-push recognizers. Experimental results demonstrate that our approach achieves higher recognition accuracies than existing approaches. © ACM 2015.

关键词： Mid-air gesture recognition pattern recognition

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Homogenization of 2D & 3D document formats for cuneiform script analysis 15

Homogenization of 2D & 3D document formats for cuneiform scr...

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3rd international Workshop on Historical Document Imaging and Processing, HIP 2015

作者： Bogacz, Bartosz Massa, Judith Mara, Hubert FCGL-Forensic Computational Geometry Laboratory IWR-Interdisciplinary Center for Scientific Computing Heidelberg University Im Neuenheimer Feld 368 Heidelberg69120 Germany

ISBN: (纸本)9781450336024

In the Digital Humanities, text sources can be digitized using various methods resulting in di erent data representations of related documents. This presents an increased challenge for clay tablets with cuneiform script, which is one of the oldest scripts written by hand, used in the ancient Middle East for more than three millennia. Using a 3D-Scanner to acquire a cuneiform tablet or a manually created line tracing are two completely di erent representations of the same type of text source. Additionally, a line tracing can be borndigital as a vector graphic or it can be a raster image of a drawing with ink on paper. Each representation is typically processed with its own tool-set and the textual analysis is therefore limited to a certain type of digital representation. In this work we present a work-ow for unification of the three most common graphical representations of cuneiform tablets. The first approach vectorizes the manually created retro-digitized tracings by skeletonization and applies pattern matching to extract the wedges, which are the radical elements of cuneiform script. Secondly, the born-digital drawings also require pattern matching as the curved lines are set di erently by each draftsperson. Due to the density of wedges, a subsequent conict resolution is applied to both types of line drawings. As cuneiform characters are written by hand in 3D, we show the segmentation and extraction of wedges from high-resolution 3D-models. The result is one representation exported as Scalable Vector Graphic (SVG), which is used for character retrieval for a future Optical Character recognition (OCR) as ultimate goal. © 2015 ACM.

关键词： Extraction

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pattern recognition in bioinformatics: 9th iapr international conference, PRIB 2014, Stockholm, Sweden, August 21-23, 2014. Proceedings 1

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丛书名： Lecture Notes in Computer Science 8626 Lecture Notes in bioinformatics

2014年

作者： Matteo Comin, Lukas Käll, Elena Marchiori, Alioune Ngom, Jagath Rajapakse (eds.)

ISBN: (数字)9783319091921

ISBN: (纸本)9783319091914;9783319091921

This book constitutes the refereed proceedings of the 8th iapr international conference on pattern recognition in bioinformatics, PRIB 2014, held in Stockholm, Sweden in August 2014. The 9 revised full papers and 9 revised short papers presented were carefully reviewed and selected from 29 submissions. The focus of the conference was on the latest Research in pattern recognition and Computational Intelligence-Based Techniques Applied to Problems in bioinformatics and Computational Biology.

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American sign language-based finger-spelling recognition using k-Nearest Neighbors classifier

American sign language-based finger-spelling recognition usi...

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international conference of Information and Communication Technology (ICoICT)

作者： Dewinta Aryanie Yaya Heryadi Computer Science Program Binus International University Jakarta Indonesia

This paper presents finger-spelling recognition method for American Sign Language (ASL) Alphabet using k-Nearest Neighbours (k-NN) Classifier. This research also examines the effect of PCA for dimensional reduction to k-NN performance. The empiric results show that k-NN classifier achieves the highest accuracy (99.8 percent) for k=3 when the pattern is represented by full dimensional feature. However, k-NN classifier only achieves 28.6 percent accuracy (for k=5) when the pattern is represented by PCAreduced dimensional feature. This low accuracy is due to several factors, among others, is the presence of high numbers of redundant or highly correlated features among ASL alphabet that makes PCA unable to separate data. Although kNN classifier accuracy is higher than the proposed classifier in [7], recognition time of k-NN classifier is longer than that of the method proposed in [7]. Therefore, k-NN classifier is suitable for early child education-based application such as self-assessment system for special need student who learns ASL alphabet finger-spelling.

关键词： Assistive technology Gesture recognition Accuracy Thumb Principal component analysis Feature extraction

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第3届亚洲模式识别会议（英文）

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智能系统学报 2015年第3期10卷 453-453页

The 3rd iapr Asian conference on pattern recognition(ACPR2015),sponsored by the international Association of pattern recognition(iapr)and supported by the Malaysian Image Analysis and Machine Intelligence Association(MIAMI)and IEEE Computational Intelligence Society(CIS)Malaysia Chapter will be held on November 3-6,2015,Kuala Lumpur,*** First Asian conference on pattern recognition(ACPR2011)was held at Beijing,China;while the second series(ACPR2013)was held at Okinawa,Japan.

关键词：第3届亚洲模式识别会议智能系统发展现状技术创新

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