Download or read book Artificial Neural Networks and Machine Learning ICANN 2020 written by Igor Farkaš and published by Springer Nature. This book was released on 2020-10-19 with total page 901 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 12396 and 12397 constitute the proceedings of the 29th International Conference on Artificial Neural Networks, ICANN 2020, held in Bratislava, Slovakia, in September 2020.* The total of 139 full papers presented in these proceedings was carefully reviewed and selected from 249 submissions. They were organized in 2 volumes focusing on topics such as adversarial machine learning, bioinformatics and biosignal analysis, cognitive models, neural network theory and information theoretic learning, and robotics and neural models of perception and action. *The conference was postponed to 2021 due to the COVID-19 pandemic.
Download or read book Artificial Neural Networks and Machine Learning ICANN 2019 Text and Time Series written by Igor V. Tetko and published by Springer Nature. This book was released on 2019-09-09 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
Download or read book Artificial Neural Networks and Machine Learning ICANN 2014 written by Stefan Wermter and published by Springer. This book was released on 2014-08-18 with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
Download or read book Artificial Neural Networks and Machine Learning ICANN 2011 written by Timo Honkela and published by Springer. This book was released on 2011-06-13 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set LNCS 6791 and LNCS 6792 constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.
Download or read book Proceedings written by Michel Verleysen and published by Presses universitaires de Louvain. This book was released on 2015 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of International Conference on Computational Intelligence and Data Engineering written by Nabendu Chaki and published by Springer. This book was released on 2017-12-19 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents high quality research work in cutting edge technologies and most-happening areas of computational intelligence and data engineering. It contains selected papers presented at International Conference on Computational Intelligence and Data Engineering (ICCIDE 2017). The conference was conceived as a forum for presenting and exchanging ideas and results of the researchers from academia and industry onto a common platform and help them develop a comprehensive understanding of the challenges of technological advancements from different viewpoints. This book will help in fostering a healthy and vibrant relationship between academia and industry. The topics of the conference include, but are not limited to collective intelligence, intelligent transportation systems, fuzzy systems, Bayesian network, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, and speech processing.
Download or read book Machine Learning written by Marco Gori and published by Morgan Kaufmann. This book was released on 2017-11-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic knowledge bases as a collection of constraints, the book draws a path towards a deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, like in fuzzy systems. A special attention is reserved to deep learning, which nicely fits the constrained- based approach followed in this book. This book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, and includes many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.
Download or read book Machine Learning for Evolution Strategies written by Oliver Kramer and published by Springer. This book was released on 2016-05-25 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.
Download or read book Artificial Neural Networks written by Petia Koprinkova-Hristova and published by Springer. This book was released on 2014-09-02 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.
Download or read book Handbook of Digital Twins written by Zhihan Lyu and published by CRC Press. This book was released on 2024-05-29 with total page 923 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last two decades, Digital Twins (DTs) have become the intelligent representation of future development in industrial production and daily life. Consisting of over 50 chapters by more than 100 contributors, this comprehensive handbook explains the concept, architecture, design specification and application scenarios of DTs. As a virtual model of a process, product or service to pair the virtual and physical worlds, DTs allow data analysis and system monitoring by using simulations. The fast-growing technology has been widely studied and developed in recent years. Featured with centralization, integrity and dynamics, it is cost-effective to drive innovation and performance. Many fields saw the adaptation and implementation across industrial production, healthcare, smart city, transportation and logistics. World-famous enterprises such as Siemens, Tesla, ANSYS and General Electric have built smart factories and pioneered digital production, heading towards Industry 4.0. This book aims to provide an in-depth understanding and reference of DTs to technical personnel in the field, students and scholars of related majors, and general readers interested in intelligent industrial manufacturing.
Download or read book Advances in Independent Component Analysis and Learning Machines written by Ella Bingham and published by Academic Press. This book was released on 2015-05-14 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: - A unifying probabilistic model for PCA and ICA - Optimization methods for matrix decompositions - Insights into the FastICA algorithm - Unsupervised deep learning - Machine vision and image retrieval - A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning - A diverse set of application fields, ranging from machine vision to science policy data - Contributions from leading researchers in the field
Download or read book Handbook Of Unconventional Computing In 2 Volumes written by Andrew Adamatzky and published by World Scientific. This book was released on 2021-08-18 with total page 1208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Did you know that computation can be implemented with cytoskeleton networks, chemical reactions, liquid marbles, plants, polymers and dozens of other living and inanimate substrates? Do you know what is reversible computing or a DNA microscopy? Are you aware that randomness aids computation? Would you like to make logical circuits from enzymatic reactions? Have you ever tried to implement digital logic with Minecraft? Do you know that eroding sandstones can compute too?This volume reviews most of the key attempts in coming up with an alternative way of computation. In doing so, the authors show that we do not need computers to compute and we do not need computation to infer. It invites readers to rethink the computer and computing, and appeals to computer scientists, mathematicians, physicists and philosophers. The topics are presented in a lively and easily accessible manner and make for ideal supplementary reading across a broad range of subjects.
Download or read book Artificial Intelligence Applications in Specialty Crops written by Yiannis Ampatzidis and published by Frontiers Media SA. This book was released on 2022-03-02 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamic Thinking written by Gregor Schöner and published by Oxford University Press. This book was released on 2016 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book describes a new theoretical approach--Dynamic Field Theory (DFT)--that explains how people think and act"--
Download or read book Five Pillars of the Mind Redesigning Education to Suit the Brain written by Tracey Tokuhama-Espinosa and published by W. W. Norton & Company. This book was released on 2019-03-05 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of Neuromyths, a revolutionary look at teaching and learning via the logical pathways of the brain. A review of the research on brain networks reveals, surprisingly, that there are just five basic pillars through which all learning takes place: Symbols, Patterns, Order, Categories, and Relationships. Dr. Tokuhama-Espinosa proposes that redesigning school curriculum around these five pillars—whether to augment or replace traditional subject categories—could enable students to develop the transdisciplinary problem-solving skills that are often touted as the ultimate goal of education. Heralding a potential paradigm shift in education, Five Pillars of the Mind explores how aligning instruction with the brain's natural design might just be the key to improving students' learning outcomes.
Download or read book Genomics at the Nexus of AI Computer Vision and Machine Learning written by Shilpa Choudhary and published by John Wiley & Sons. This book was released on 2024-10-01 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a comprehensive understanding of cutting-edge research and applications at the intersection of genomics and advanced AI techniques and serves as an essential resource for researchers, bioinformaticians, and practitioners looking to leverage genomics data for AI-driven insights and innovations. The book encompasses a wide range of topics, starting with an introduction to genomics data and its unique characteristics. Each chapter unfolds a unique facet, delving into the collaborative potential and challenges that arise from advanced technologies. It explores image analysis techniques specifically tailored for genomic data. It also delves into deep learning showcasing the power of convolutional neural networks (CNN) and recurrent neural networks (RNN) in genomic image analysis and sequence analysis. Readers will gain practical knowledge on how to apply deep learning techniques to unlock patterns and relationships in genomics data. Transfer learning, a popular technique in AI, is explored in the context of genomics, demonstrating how knowledge from pre-trained models can be effectively transferred to genomic datasets, leading to improved performance and efficiency. Also covered is the domain adaptation techniques specifically tailored for genomics data. The book explores how genomics principles can inspire the design of AI algorithms, including genetic algorithms, evolutionary computing, and genetic programming. Additional chapters delve into the interpretation of genomic data using AI and ML models, including techniques for feature importance and visualization, as well as explainable AI methods that aid in understanding the inner workings of the models. The applications of genomics in AI span various domains, and the book explores AI-driven drug discovery and personalized medicine, genomic data analysis for disease diagnosis and prognosis, and the advancement of AI-enabled genomic research. Lastly, the book addresses the ethical considerations in integrating genomics with AI, computer vision, and machine learning. Audience The book will appeal to biomedical and computer/data scientists and researchers working in genomics and bioinformatics seeking to leverage AI, computer vision, and machine learning for enhanced analysis and discovery; healthcare professionals advancing personalized medicine and patient care; industry leaders and decision-makers in biotechnology, pharmaceuticals, and healthcare industries seeking strategic insights into the integration of genomics and advanced technologies.
Download or read book Image Processing and Pattern Recognition Based on Parallel Shift Technology written by Stepan Bilan and published by CRC Press. This book was released on 2018-01-29 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical operations to allow the generation of a minimum set of features to describe and recognize the image. This book also describes the theoretical foundations of parallel shift technology and pattern recognition. Based on these methods and theories, this book is intended to help researchers with artificial intelligence systems design, robotics, and developing software and hardware applications.
