Výsledky vyhľadávania - Computer Learning AND Pattern Recognition::Neural Networks*

  1. 1

    Complex-Valued Neural Networks: A Comprehensive Survey Autor Lee, ChiYan, Hasegawa, Hideyuki, Gao, Shangce

    ISSN: 2329-9266, 2329-9274
    Vydavateľské údaje: Piscataway Chinese Association of Automation (CAA) 01.08.2022
    Vydané v IEEE/CAA journal of automatica sinica (01.08.2022)
    “…Complex-valued neural networks (CVNNs) have shown their excellent efficiency compared to their real counter-parts in speech enhancement, image and signal processing…”
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    Automatic Recognition of Speed Limits on Speed-Limit Signs by Using Machine Learning Autor Miyata, Shigeharu

    ISSN: 2313-433X, 2313-433X
    Vydavateľské údaje: Basel MDPI AG 01.09.2017
    Vydané v Journal of Imaging (01.09.2017)
    “… This method consists of the following three processes: first (1) a method of detecting the speed-limit signs with a machine learning method utilizing the local binary pattern (LBP…”
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    A survey of robust adversarial training in pattern recognition: Fundamental, theory, and methodologies Autor Qian, Zhuang, Huang, Kaizhu, Wang, Qiu-Feng, Zhang, Xu-Yao

    ISSN: 0031-3203, 1873-5142
    Vydavateľské údaje: Elsevier Ltd 01.11.2022
    Vydané v Pattern recognition (01.11.2022)
    “… Deep neural networks have achieved remarkable success in machine learning, computer vision, and pattern recognition in the last few decades…”
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  4. 4

    Deep Learning Framework for Classification of Emoji Based Sentiments Autor Parveen Shaikh, Nighat, Hussain Mahar, Mumtaz

    ISSN: 1546-2226, 1546-2218, 1546-2226
    Vydavateľské údaje: Henderson Tech Science Press 2022
    “…Recent patterns of human sentiments are highly influenced by emoji based sentiments (EBS…”
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    Navegación autónoma del Robot KUKA Youbot con señalización basada en técnicas de detección de objetos y redes neuronales profundas Autor Encalada, Patricio, Gordón, Carlos, Lema, Henry, León, Diego, Chicaiza, Dennis

    ISSN: 1646-9895
    Vydavateľské údaje: Lousada Associação Ibérica de Sistemas e Tecnologias de Informacao 01.04.2019
    “… los vehículos comerciales en industriales. En el texto Autonomous robot navigation based on pattern recognition techniques and artificial neural networks, de Quiñonez et al…”
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    Comparison of Different Learning Algorithms for Pattern Recognition with Hopfield's Neural Network Autor Szandała, Tomasz

    ISSN: 1877-0509, 1877-0509
    Vydavateľské údaje: Elsevier B.V 2015
    Vydané v Procedia computer science (2015)
    “…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…”
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    A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition Autor Zhang, Yong, Li, Peng, Jin, Yingyezhe, Choe, Yoonsuck

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Vydavateľské údaje: United States IEEE 01.11.2015
    “… With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression…”
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    Hybrid methods in pattern recognition (Series in machine perception and artificial intelligence - vol. 47) Autor Bunke, H, Kandel, A

    ISBN: 9789810248321, 9810248326, 9812778144, 9789812778147
    Vydavateľské údaje: New Jersey World Scientific Publishing Co. Pte. Ltd 2002
    “…The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago…”
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    E-kniha Kniha
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    VERİ MADENCİLİĞİNDE SINIFLANDIRMA ALGORİTMALARININ PERFORMANS DEĞERLENDİRMESİ VE R DİLİ İLE BİR UYGULAMA Autor ÇINAR, Ayşe

    ISSN: 1300-0845, 2147-5377
    Vydavateľské údaje: Istanbul Marmara University Institute of Social Sciences 01.01.2019
    Vydané v Öneri (01.01.2019)
    “…Sınıflandırma Yöntemi, veri madenciliğinin başlıca yöntemlerinden biri olup, öğrenme algoritmasına dayanır. Büyük ölçekli bir veri içinde gizli kalmış bir…”
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    Data-driven emergence of convolutional structure in neural networks Autor Ingrosso, Alessandro, Goldt, Sebastian

    ISSN: 1091-6490, 1091-6490
    Vydavateľské údaje: United States 04.10.2022
    “…Exploiting data invariances is crucial for efficient learning in both artificial and biological neural circuits…”
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    Parallel ensemble learning of convolutional neural networks and local binary patterns for face recognition Autor Tang, Jialin, Su, Qinglang, Su, Binghua, Fong, Simon, Cao, Wei, Gong, Xueyuan

    ISSN: 0169-2607, 1872-7565, 1872-7565
    Vydavateľské údaje: Ireland Elsevier B.V 01.12.2020
    “… A new face recognition method based on parallel ensemble learning of convolutional neural networks (CNN…”
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    Hands-on Machine Learning with Python - Implement Neural Network Solutions with Scikit-Learn and PyTorch Autor Ashwin Pajankar, Aditya Joshi

    ISBN: 9781484279205, 1484279204, 1484279212, 9781484279212
    Vydavateľské údaje: Berkeley, CA Apress, an imprint of Springer Nature 2022
    “…Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning…”
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    E-kniha
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    Automated Malignant Melanoma Classification Using Convolutional Neural Networks Autor Camacho, Edgar, Guarnizo Marín, José Guillermo, Riaño Borda, Sebastián, Mateus Rojas, Armando

    ISSN: 0124-8170
    Vydavateľské údaje: 2022
    “…En esta investigación se propone un diseño de arquitectura para el reconocimiento de melanoma (un tipo de cáncer de piel) mediante el uso de una CNN (Red…”
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    Practical emotional neural networks Autor Lotfi, Ehsan, Akbarzadeh-T., M.-R.

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Vydavateľské údaje: Kidlington Elsevier Ltd 01.11.2014
    Vydané v Neural networks (01.11.2014)
    “…In this paper, we propose a limbic-based artificial emotional neural network (LiAENN) for a pattern recognition problem…”
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    Deep learning in neural networks: An overview Autor Schmidhuber, Jürgen

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Vydavateľské údaje: United States Elsevier Ltd 01.01.2015
    Vydané v Neural networks (01.01.2015)
    “…In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning…”
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    Machine learning algorithms to infer trait‐matching and predict species interactions in ecological networks Autor Pichler, Maximilian, Boreux, Virginie, Klein, Alexandra‐Maria, Schleuning, Matthias, Hartig, Florian, Carvalheiro, Luisa

    ISSN: 2041-210X, 2041-210X
    Vydavateľské údaje: London John Wiley & Sons, Inc 01.02.2020
    Vydané v Methods in ecology and evolution (01.02.2020)
    “… Using simulated and real data, we contrast conventional generalized linear models (GLM) with more flexible Machine Learning…”
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    A New Method of Mixed Gas Identification Based on a Convolutional Neural Network for Time Series Classification Autor Han, Lu, Yu, Chongchong, Xiao, Kaitai, Zhao, Xia

    ISSN: 1424-8220, 1424-8220
    Vydavateľské údaje: Switzerland MDPI AG 26.04.2019
    Vydané v Sensors (Basel, Switzerland) (26.04.2019)
    “… In view of the superiority of convolutional neural networks in the field of computer vision, we applied the concept to the classification of five mixed gas time series data collected by an array…”
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    Deep Neural Message Passing With Hierarchical Layer Aggregation and Neighbor Normalization Autor Fan, Xiaolong, Gong, Maoguo, Tang, Zedong, Wu, Yue

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Vydavateľské údaje: United States IEEE 01.12.2022
    “…As a unified framework for graph neural networks, message passing-based neural network (MPNN…”
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    Noise Immunity and Robustness Study of Image Recognition Using a Convolutional Neural Network Autor Ziyadinov, Vadim, Tereshonok, Maxim

    ISSN: 1424-8220, 1424-8220
    Vydavateľské údaje: Switzerland MDPI AG 06.02.2022
    Vydané v Sensors (Basel, Switzerland) (06.02.2022)
    “… We also examined the noise immunity of convolutional neural networks and estimated the influence of uncertainty in the training and testing datasets on recognition probability…”
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