Neural networks (Computer science)
概要
作品: | 493 作品在 200 項出版品 200 種語言 |
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書目資訊
Learning algorithms : = theory and applications in signal processing, control, and communications /
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Solving problems in environmental engineering and geosciences with artificial neural networks
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Neural networks in C++ : = an object-oriented framework for building connectionist systems /
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Learning and coordination : = enhancing agent performance through distributed decision making /
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Computational architectures integrating neural and symbolic processes : = a perspective on the state of the art /
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Trading on the edge : = neural, genetic, and fuzzy systems for chaotic financial markets /
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Neural networks and fuzzy systems : = a dynamical systems approach to machine intelligence /
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Parallel algorithms : = for digital image processing, computer vision and neural networks /
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Neural smithing : = supervised learning in feedforward artificial neural networks /
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Supervised and unsupervised pattern recognition : = feature extraction and computational intelligence /
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Neural computation of pattern motion = modeling stages of motion analysis in the primate visual cortex /
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Neural engineering = computation, representation, and dynamics in neurobiological systems /
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
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Complex networks = results of 2009 International Workshop on Complex Networks (CompleNet 2009) /
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Neural networks in multidimensional domains = fundamentals and new trends in modelling and control /
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Scientific applications of neural nets = proceedings of the 194th W.E. Heraeus Seminar held at Bad Honnef, Germany, 11-13 May 1998 /
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Emergent neural computational architectures based on neuroscience = towards neuroscience-inspired computing /
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Dynamics on and of complex networks = applications to biology, computer science, and the social sciences /
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Artificial neural networks - ICANN 2010 = 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, proceedings.. Part III /
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Neural information processing = theory and algorithms : 17th International Conference, ICONIP 2010, Sydney, Australia, November 22-25, 2010, proceedings.. Part I/
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Artificial higher order neural networks for computer science and engineering = trends for emerging applications /
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Brain informatics = international conference, BI 2012, Macau, China, December 4-7, 2012 : proceedings /
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Neural nets WIRN09 = proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy May 28-30 2009 /
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Cognitive informatics in health and biomedicine = case studies on critical care, complexity and errors /
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Brain informatics and health = International Conference, BIH 2014, Warsaw, Poland, August 11-14, 2014 : proceedings /
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Wavelet neural networks = with applications in financial engineering, chaos, and classification /
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Bayesian statistics from methods to models and applications = research from BAYSM 2014 /
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Multiple classifier systems = 12th International Workshop, MCS 2015, Gunzburg, Germany, June 29 - July 1, 2015 : proceedings /
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Design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization
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Fuzzy neural networks for real time control applications = concepts, modeling and algorithms for fast learning /
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Guide to convolutional neural networks = a practical application to traffic-sign detection and classification /
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Neuro-fuzzy and soft computing : = a computational approach to learning and machine intelligence /
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New soft computing techniques for system modeling, pattern classification and image processing /
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Neural networks in finance and investing : = using artificial intelligence to improve real-world performance /
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Neuro-fuzzy and soft computing : = a computational approach to learning and machine intelligence /
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Information dynamics in cognitive, psychological, social and anomalous phenomena /
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Computational architectures integrating neural and symbolic processes = a perspective on the state of the art /
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Solving problems in environmental engineering and geosciences with artificial neural networks
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Biological and Artificial Intelligence Environments = 15th Italian Workshop on Neural Nets, WIRN VIETRI 2004 /
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Identification of Nonlinear Systems Using Neural Networks and Polynomial Models = A Block-Oriented Approach /
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Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing = An Evolutionary Approach for Neural Networks and Fuzzy Systems /
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Neural network-based state estimation of nonlinear systems = application to fault detection and isolation /
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New directions in neural networks = 18th Italian Workshop on Neural Networks: WIRN 2008 /
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Artificial neural networks - ICANN 2010 = 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, proceedings.. Part I /
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Brain informatics = International Conference, BI 2010, Toronto, ON, Canada, August 28-30, 2010, proceedings /
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Latent variable analysis and signal separation = 9th International Conference, LVA/ICA 2010, St. Malo, France, September 27-30, 2010, proceedings /
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Artificial neural networks - ICANN 2010 = 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, proceedings.. Part II /
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Uncertainty treatment using paraconsistent logic = introducing paraconsistent artificial neural networks /
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Intelligent control = a hybrid approach based on fuzzy logic, neural networks and genetic algorithms /
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Proceedings of the fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014
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Growing adaptive machines = combining development and learning in artificial neural networks /
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Isospectral transformations = a new approach to analyzing multidimensional systems and networks /
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Paraconsistent intelligent-based systems = new trends in the applications of paraconsistency /
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Neural information processing = 22nd International Conference, ICONIP 2015, November 9-12, 2015 : proceedings.. Part IV /
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Wavelet neural networks : = with applications in financial engineering, chaos, and classification /
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Practical convolutional neural networks : = implement advanced deep learning models using Python /
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Deep learning for computer vision : = expert techniques to train advanced neural networks using TensorFlow and Keras /
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Recurrent neural networks for short-term load forecasting = an overview and comparative analysis /
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Neural networks for modelling and control of dynamic systems : = a practitioner's handbook /
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New hybrid intelligent systems for diagnosis and risk evaluation of arterial hypertension
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Learn Keras for deep neural networks = a fast-track approach to modern deep learning with Python /
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Artificial neural networks with Java = tools for building neural network applications /
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Deep neuro-fuzzy systems with Python = with case studies and applications from the industry /
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Effective statistical learning methods for actuaries.. III,. Neural networks and extensions
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Deep learning projects using TensorFlow 2 = neural network development with Python and Keras /
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Artificial intelligence systems based on hybrid neural networks = theory and applications /
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Estimating functional connectivity and topology in large-scale neuronal assemblies = statistical and computational methods /
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Artificial neural networks with TensorFlow 2 = ANN architecture machine learning projects /
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Convolutional neural networks with Swift for Tensorflow = image recognition and dataset categorization /
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Hands-on question answering systems with BERT = applications in neural networks and natural language processing /
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Fuzzy logic hybrid extensions of neural and optimization algorithms = theory and applications /
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Using artificial neural networks for timeseries smoothing and forecasting = case studies in economics /
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Artificial mathematical intelligence = cognitive, (meta)mathematical, physical and philosophical foundations /
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Artificial neural networks with Java = tools for building neural network applications /
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Applied deep learning with TensorFlow 2 = learn to implement advanced deep learning techniques with Python /
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Deep neural networks and data for automated driving = robustness, uncertainty quantification, and insights towards safety /
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Automated deep learning using neural network intelligence = develop and design pytorch and tensorflow models using python /
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New perspectives on hybrid intelligent system design based on fuzzy logic, neural networks and metaheuristics
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Artificial neural networks and structural equation modeling = marketing and consumer research applications /
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Complex-valued neural networks systems with time delay = stability analysis and (anti-)synchronization control /
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Biomedical and business applications using artificial neural networks and machine learning
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Pattern recognition using neural networks : = theory and algorithms for engineers and scientists /
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Recurrent neural networks for prediction : = learning algorithms, architectures, and stability /
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Applied Recommender Systems with Python = Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques /
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PyTorch recipes = a problem-solution approach to build, train and deploy neural network models /
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The book of GENESIS : = exploring realistic neural models with the GEneral NEural SImulation System /
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Fundamentals of natural computing : = basic concepts, algorithms, and applications /
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Neural engineering : = computation, representation, and dynamics in neurobiological systems /
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Shallow and deep learning principles = scientific, philosophical, and logical perspectives /
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Building computer vision applications using artificial neural networks = with examples in OpenCV and TensorFlow with Python /
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Function approximation using generalized adalines : = fundamental multi-state neural organizations /
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Fuzzy logic augmentation of neural and optimization algorithms = theoretical aspects and real applications /
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New classification method based on modular neural networks with the LVQ algorithm and type-2 fuzzy logic
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Deep Belief Nets in C++ and CUDA C.. Volume 1,. Restricted Boltzmann machines and supervised feedforward networks
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Deep learning with PyTorch : = a practical approach to building neural network models using PyTorch /
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Deep learning and convolutional neural networks for medical imaging and clinical informatics
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Images as data for social science research : = an introduction to convolutional neural nets for image classification /
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Machine learning in social networks = embedding nodes, edges, communities, and graphs /
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Principles of high-performance processor design = for high performance computing, deep neural networks and data science /
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A few things I know about her = a personally machine learning inspired approach to understand surrounding nature /
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Images as data for social science research = an introduction to convolutional neural nets for image classification /
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Banach space valued neural network = ordinary and fractional approximation and interpolation /
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