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检索条件"任意字段=3rd IAPR Workshop on Artificial Neural Networks in Pattern Recognition"
274 条 记 录,以下是91-100 订阅
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Extracting Gamma-Ray Information from Images with Convolutional neural Network Methods on Simulated Cherenkov Telescope Array Data  8th
Extracting Gamma-Ray Information from Images with Convolutio...
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8th iapr TC3 workshop on artificial neural networks in pattern recognition (ANNPR)
作者: Mangano, Salvatore Delgado, Carlos Isabel Bernardos, Maria Lallena, Miguel Rodriguez Vazquez, Juan Jose CIEMAT Ctr Invest Energet Medioambientales & Tecn Av Complutense 40 Madrid 28040 Spain
The Cherenkov Telescope Array (CTA) will be the world's leading ground-based gamma-ray observatory allowing us to study very high energy phenomena in the Universe. CTA will produce huge data sets, of the order of ... 详细信息
来源: 评论
Maximum-Likelihood Estimation of neural Mixture Densities: Model, Algorithm, and Preliminary Experimental Evaluation  8th
Maximum-Likelihood Estimation of Neural Mixture Densities: M...
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8th iapr TC3 workshop on artificial neural networks in pattern recognition (ANNPR)
作者: Trentin, Edmondo Univ Siena Dipartimento Ingn Informaz & Sci Matemat Siena Italy
Unsupervised estimation of probability density functions by means of parametric mixture densities (e.g., Gaussian mixture models) may improve significantly over plain, single-density estimators in terms of modeling ca... 详细信息
来源: 评论
A Hidden Markov Model Based Approach for Facial Expression recognition in Image Sequences
A Hidden Markov Model Based Approach for Facial Expression R...
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4th workshop on artificial neural networks in pattern recognition
作者: Schmidt, Miriam Schels, Martin Schwenker, Friedhelm Univ Ulm Inst Neural Informat Proc D-89069 Ulm Germany
One of the important properties of hidden Markov models is the ability to model sequential dependencies. In this study the applicability of hidden Markov models for emotion recognition in image sequences is investigat... 详细信息
来源: 评论
Towards Effective Classification of Imbalanced Data with Convolutional neural networks  7th
Towards Effective Classification of Imbalanced Data with Con...
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7th iapr TC3 workshop on artificial neural networks in pattern recognition (ANNPR)
作者: Raj, Vidwath Magg, Sven Wermter, Stefan Univ Hamburg Dept Informat Knowledge Technol Hamburg Germany
Class imbalance in machine learning is a problem often found with real-world data, where data from one class clearly dominates the dataset. Most neural network classifiers fail to learn to classify such datasets corre... 详细信息
来源: 评论
recognition of Sequences of Graphical patterns
Recognition of Sequences of Graphical Patterns
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4th workshop on artificial neural networks in pattern recognition
作者: Trentin, Edmondo Zhang, ShuJia Hagenbuchner, Markus DII Univ Siena V Roma 56 Siena Italy Univ Wollongong Wollongong NSW 2522 Australia
Several real-world problems (e.g., in bioinformatics/proteomics, or in recognition of video sequences) can be described as classification tasks over sequences of structured data, i.e. sequences of graphs, in a natural... 详细信息
来源: 评论
Fusers Based on Classifier Response and Discriminant Function - Comparative Study
Fusers Based on Classifier Response and Discriminant Functio...
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3rd International workshop on Hybrid artificial Intelligence Systems
作者: Wozniak, Michal Jackowski, Konrad Wroclaw Univ Technol Chair Syst & Comp Networks PL-50370 Wroclaw Poland
The Multiple Classifier Systems are nowadays one of the most promising directions in pattern recognition. There are many methods of decision making by the ensemble of classifiers. The most popular are methods that hav... 详细信息
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Polyphonic monotimbral music transcription using dynamic networks
Polyphonic monotimbral music transcription using dynamic net...
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1st iapr TC3 workshop on artificial neural networks in pattern recognition
作者: Pertusa, A Inesta, JM Univ Alicante Dept Lenguajes & Sistemas Informat E-03080 Alicante Spain
The automatic extraction of the notes that were played in a digital musical signal (automatic music transcription) is an open problem. A number of techniques have been applied to solve it without concluding results. T... 详细信息
来源: 评论
Trace and Detect Adversarial Attacks on CNNs Using Feature Response Maps  8th
Trace and Detect Adversarial Attacks on CNNs Using Feature R...
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8th iapr TC3 workshop on artificial neural networks in pattern recognition (ANNPR)
作者: Amirian, Mohammadreza Schwenker, Friedhelm Stadelmann, Thilo ZHAW Datalab & Sch Engn Winterthur Switzerland Ulm Univ Inst Neural Informat Proc Ulm Germany
The existence of adversarial attacks on convolutional neural networks (CNN) questions the fitness of such models for serious applications. The attacks manipulate an input image such that misclassification is evoked wh... 详细信息
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Maximum Echo-State-Likelihood networks for Emotion recognition
Maximum Echo-State-Likelihood Networks for Emotion Recogniti...
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4th workshop on artificial neural networks in pattern recognition
作者: Trentin, Edmondo Scherer, Stefan Schwenker, Friedhelm Univ Siena Dipartimento Ingn Informazione Via Laterina 8 I-53100 Siena Italy Univ Ulm Inst Neural Informa Proc D-89069 Ulm Germany
Emotion recognition is a relevant task in human-computer interaction. Several pattern recognition and machine learning techniques have been applied so far in order to assign input audio and/or video sequences to speci... 详细信息
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Prediction of insertion-site preferences of transposons using support vector machines and artificial neural networks  6
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6th iapr TC3 International workshop on artificial neural networks for pattern recognition, ANNPR 2014
作者: Ayat, Maryam Domaratzki, Michael Bioinformatics Lab Department of Computer Science University of Manitoba WinnipegMB R3T 2N2 Canada
Transposons are segments of DNA that are capable of moving from one location to another within the genome of a cell. Understanding transposon insertion-site preferences is critically important in functional genomics a... 详细信息
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