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State Of The Art In Neural Networks And Their Applications

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State of the Art in Neural Networks and Their Applications

State of the Art in Neural Networks and Their Applications Book
Author : Ayman S. El-Baz,Jasjit S. Suri
Publisher : Academic Press
Release : 2021-07-21
ISBN : 0128218495
Language : En, Es, Fr & De

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Book Description :

State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. Advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing and suitable data analytics useful for clinical diagnosis and research applications are covered, including relevant case studies. The application of Neural Network, Artificial Intelligence, and Machine Learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume 1 covers the state-of-the-art deep learning approaches for the detection of renal, retinal, breast, skin, and dental abnormalities and more. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), with coverage of computer-aided classification, Unified Deep Learning Frameworks, mammography, fundus imaging, optical coherence tomography, cryo-electron tomography, 3D MRI, CT, and more. Covers deep learning for several medical conditions including renal, retinal, breast, skin, and dental abnormalities, Medical Image Analysis, as well as detection, segmentation, and classification via AI.

State of the Art in Neural Networks and Their Applications

State of the Art in Neural Networks and Their Applications Book
Author : Jasjit S. Suri,Ayman S. El-Baz
Publisher : Elsevier
Release : 2022-12-09
ISBN : 0128199121
Language : En, Es, Fr & De

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Book Description :

State of the Art in Neural Networks and Their Applications, Volume Two presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. The book provides over views and case studies of advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing, and suitable data analytics useful for clinical diagnosis and research applications. The application of neural network, artificial intelligence and machine learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume One: Neural Networks in Oncology Imaging covers lung cancer, prostate cancer, and bladder cancer. Volume Two: Neural Networks in Brain Disorders and Other Diseases covers autism spectrum disorder, Alzheimer’s disease, attention deficit hyperactivity disorder, hypertension, and other diseases. Written by experienced engineers in the field, these two volumes will help engineers, computer scientists, researchers, and clinicians understand the technology and applications of artificial neural networks. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of oncology imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), including coverage of computer-aided classification, unified deep learning frameworks, 3D MRI, PET/CT, and more Covers deep learning cancer identification from histopathological images, medical image analysis, detection, segmentation and classification via AI

State of the Art in Neural Networks and Their Applications

State of the Art in Neural Networks and Their Applications Book
Author : Jasjit S. Suri,Ayman S.El-Baz
Publisher : Academic Press
Release : 2022-11-29
ISBN : 9780128199121
Language : En, Es, Fr & De

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Book Description :

State of the Art in Neural Networks and Their Applications, Volume Two presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. The book provides over views and case studies of advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing, and suitable data analytics useful for clinical diagnosis and research applications. The application of neural network, artificial intelligence and machine learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume One: Neural Networks in Oncology Imaging covers lung cancer, prostate cancer, and bladder cancer. Volume Two: Neural Networks in Brain Disorders and Other Diseases covers autism spectrum disorder, Alzheimer’s disease, attention deficit hyperactivity disorder, hypertension, and other diseases. Written by experienced engineers in the field, these two volumes will help engineers, computer scientists, researchers, and clinicians understand the technology and applications of artificial neural networks. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of oncology imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), including coverage of computer-aided classification, unified deep learning frameworks, 3D MRI, PET/CT, and more Covers deep learning cancer identification from histopathological images, medical image analysis, detection, segmentation and classification via AI

Complex Networks and Their Applications VIII

Complex Networks and Their Applications VIII Book
Author : Hocine Cherifi,Sabrina Gaito,José Fernendo Mendes,Esteban Moro,Luis Mateus Rocha
Publisher : Springer Nature
Release : 2019-11-26
ISBN : 3030366839
Language : En, Es, Fr & De

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Book Description :

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the Eighth International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2019), which took place in Lisbon, Portugal, on December 10–12, 2019. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, and network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.

Business Applications of Neural Networks

Business Applications of Neural Networks Book
Author : Paulo J. G. Lisboa,Bill Edisbury,Alfredo Vellido
Publisher : World Scientific
Release : 2000
ISBN : 9810240899
Language : En, Es, Fr & De

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Book Description :

Neural networks are increasingly being used in real-world business applications and, in some cases, such as fraud detection, they have already become the method of choice. Their use for risk assessment is also growing and they have been employed to visualise complex databases for marketing segmentation. This boom in applications covers a wide range of business interests -- from finance management, through forecasting, to production. The combination of statistical, neural and fuzzy methods now enables direct quantitative studies to be carried out without the need for rocket-science expertise. This book reviews the state-of-the-art in current applications of neural-network methods in three important areas of business analysis. It includes a tutorial chapter to introduce new users to the potential and pitfalls of this new technology.

Complex Networks and Their Applications VII

Complex Networks and Their Applications VII Book
Author : Luca Maria Aiello,Chantal Cherifi,Hocine Cherifi,Renaud Lambiotte,Pietro Lió,Luis M. Rocha
Publisher : Springer
Release : 2018-12-05
ISBN : 3030054144
Language : En, Es, Fr & De

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Book Description :

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge on December 11–13, 2018. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure and network dynamics; diffusion, epidemics and spreading processes; and resilience and control; as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.

Complex Networks Their Applications X

Complex Networks   Their Applications X Book
Author : Rosa Maria Benito,Chantal Cherifi,Hocine Cherifi,Esteban Moro,Luis M. Rocha,Marta Sales-Pardo
Publisher : Springer Nature
Release : 2022-01-01
ISBN : 3030934098
Language : En, Es, Fr & De

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Book Description :

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.

Cellular Neural Networks and Their Applications

Cellular Neural Networks and Their Applications Book
Author : Ronald Tetzlaff
Publisher : World Scientific
Release : 2002
ISBN : 981238121X
Language : En, Es, Fr & De

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Book Description :

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).

Reconfigurable Cellular Neural Networks and Their Applications

Reconfigurable Cellular Neural Networks and Their Applications Book
Author : Müştak E. Yalçın,Tuba Ayhan,Ramazan Yeniçeri
Publisher : Springer
Release : 2019-04-15
ISBN : 3030178404
Language : En, Es, Fr & De

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Book Description :

This book explores how neural networks can be designed to analyze sensory data in a way that mimics natural systems. It introduces readers to the cellular neural network (CNN) and formulates it to match the behavior of the Wilson–Cowan model. In turn, two properties that are vital in nature are added to the CNN to help it more accurately deliver mimetic behavior: randomness of connection, and the presence of different dynamics (excitatory and inhibitory) within the same network. It uses an ID matrix to determine the location of excitatory and inhibitory neurons, and to reconfigure the network to optimize its topology. The book demonstrates that reconfiguring a single-layer CNN is an easier and more flexible solution than the procedure required in a multilayer CNN, in which excitatory and inhibitory neurons are separate, and that the key CNN criteria of a spatially invariant template and local coupling are fulfilled. In closing, the application of the authors’ neuron population model as a feature extractor is exemplified using odor and electroencephalogram classification.

Advances in Neural Networks ISNN 2019

Advances in Neural Networks     ISNN 2019 Book
Author : Huchuan Lu,Huajin Tang,Zhanshan Wang
Publisher : Springer
Release : 2019-06-26
ISBN : 3030228088
Language : En, Es, Fr & De

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Book Description :

This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.

Cellular Neural Networks and Their Applications

Cellular Neural Networks and Their Applications Book
Author : Ronald Tetzlaff
Publisher : World Scientific
Release : 2002-07-08
ISBN : 9814487767
Language : En, Es, Fr & De

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Book Description :

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000). Contents:On the Relationship Between CNNs and PDEs (M Gilli et al.)Moving Object Tracking on Panoramic Images (P Földesy et al.)Emergence of Global Patterns in Connected Neural Networks (T Shimizu)Configurable Multi-Layer CNN-UM Emulator on FPGA (Z Nagy & P Szolgay)A CNN Based System to Blind Sources Separation of MEG Signals (M Bucolo et al.)Time as Coding Space for Information Processing in the Cerebral Cortex (W Singer)Analyzing Multidimensional Neural Activity via CNN-UM (V Gál et al.)Visual Feedback by Using a CNN Chip Prototype System (P Arena et al.)Computational and Computer Complexity of Analogic Cellular Wave Computers (T Roska)Chaotic Phenomena in Quantum Cellular Neural Networks (L Fortuna & D Porto)Fingerprint Image Enhancement Using CNN Gabor-Type Filters (E Saatci & V Tavsanoglu)CNN Based Color Constancy Algorithm (L Török & Á Zarándy)Statistical Error Modeling of CNN-UM Architectures: The Grayscale Case (P Földesy)MEMS, Microsystems and Nanosystems (M E Zaghloul)Texture Segmentation by the 64x64 CNN Chip (T Szirányi)Teaching CNN and Learning by Using CNN (P Arena et al.)Novel Methods and Results in Training Universal Multi-Nested Neurons (R Dogaru et al.)Test-Bed Board for 16x64 Stereo Vision CNN Chip (M Salerno et al.)and other papers Readership: Graduate students, researchers, lecturers and industrialists. Keywords:

Complex Valued Neural Networks with Multi Valued Neurons

Complex Valued Neural Networks with Multi Valued Neurons Book
Author : Igor Aizenberg
Publisher : Springer
Release : 2011-06-24
ISBN : 3642203531
Language : En, Es, Fr & De

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Book Description :

Complex-Valued Neural Networks have higher functionality, learn faster and generalize better than their real-valued counterparts. This book is devoted to the Multi-Valued Neuron (MVN) and MVN-based neural networks. It contains a comprehensive observation of MVN theory, its learning, and applications. MVN is a complex-valued neuron whose inputs and output are located on the unit circle. Its activation function is a function only of argument (phase) of the weighted sum. MVN derivative-free learning is based on the error-correction rule. A single MVN can learn those input/output mappings that are non-linearly separable in the real domain. Such classical non-linearly separable problems as XOR and Parity n are the simplest that can be learned by a single MVN. Another important advantage of MVN is a proper treatment of the phase information. These properties of MVN become even more remarkable when this neuron is used as a basic one in neural networks. The Multilayer Neural Network based on Multi-Valued Neurons (MLMVN) is an MVN-based feedforward neural network. Its backpropagation learning algorithm is derivative-free and based on the error-correction rule. It does not suffer from the local minima phenomenon. MLMVN outperforms many other machine learning techniques in terms of learning speed, network complexity and generalization capability when solving both benchmark and real-world classification and prediction problems. Another interesting application of MVN is its use as a basic neuron in multi-state associative memories. The book is addressed to those readers who develop theoretical fundamentals of neural networks and use neural networks for solving various real-world problems. It should also be very suitable for Ph.D. and graduate students pursuing their degrees in computational intelligence.

Encyclopedia of Computer Science and Technology

Encyclopedia of Computer Science and Technology Book
Author : Allen Kent,James G. Williams
Publisher : CRC Press
Release : 1996-07-26
ISBN : 9780824722883
Language : En, Es, Fr & De

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Book Description :

Acquiring Task-Based Knowledge and Specifications to Seek Time Evaluation

Computer Information Systems and Industrial Management

Computer Information Systems and Industrial Management Book
Author : Khalid Saeed,Władysław Homenda
Publisher : Springer
Release : 2016-09-09
ISBN : 9783319453774
Language : En, Es, Fr & De

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Book Description :

This book constitutes the proceedings of the 15th IFIP TC8 International Conference on Computer Information Systems and Industrial Management, CISIM 2016, held in Vilnius, Lithuania, in September 2016. The 63 regular papers presented together with 1 inivted paper and 5 keynotes in this volume were carefully reviewed and selected from about 89 submissions. The main topics covered are rough set methods for big data analytics; images, visualization, classification; optimization, tuning; scheduling in manufacturing and other applications; algorithms; decisions; intelligent distributed systems; and biometrics, identification, security.

Applications of Soft Computing

Applications of Soft Computing Book
Author : Erel Avineri,Mario Köppen,Keshav Dahal,Yos Sunitiyoso,Rajkumar Roy
Publisher : Springer Science & Business Media
Release : 2008-12-28
ISBN : 3540880798
Language : En, Es, Fr & De

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Book Description :

Soft Computing is a complex of methodologies that includes artificial neural networks, genetic algorithms, fuzzy logic, Bayesian networks, and their hybrids. It admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic the remarkable human capability of making decisions in real-life, ambiguous environments. Soft Computing has therefore become popular in developing systems that encapsulate human expertise. 'Applications of Soft Computing: Updating the State of Art' contains a collection of papers that were presented at the 12th On-line World Conference on Soft Computing in Industrial Applications, held in October 2007. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including design, intelligent control, optimization, signal processing, pattern recognition, computer graphics, production, as well as civil engineering and applications to traffic and transportation systems. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.

Artificial Neural Networks for Renewable Energy Systems and Real World Applications

Artificial Neural Networks for Renewable Energy Systems and Real World Applications Book
Author : Ammar Hamed Elsheikh,Mohamed Elasyed Abd Elaziz
Publisher : Academic Press
Release : 2022-09-08
ISBN : 0128231866
Language : En, Es, Fr & De

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Book Description :

Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis. Includes illustrative examples on the design and development of ANNS for renewable and manufacturing applications Features computer-aided simulations presented as algorithms, pseudocodes and flowcharts Covers ANN theory for easy reference in subsequent technology specific sections

Current Perspectives and New Directions in Mechanics Modelling and Design of Structural Systems

Current Perspectives and New Directions in Mechanics  Modelling and Design of Structural Systems Book
Author : Alphose Zingoni
Publisher : CRC Press
Release : 2022-09-02
ISBN : 1000824365
Language : En, Es, Fr & De

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Book Description :

Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems comprises 330 papers that were presented at the Eighth International Conference on Structural Engineering, Mechanics and Computation (SEMC 2022, Cape Town, South Africa, 5-7 September 2022). The topics featured may be clustered into six broad categories that span the themes of mechanics, modelling and engineering design: (i) mechanics of materials (elasticity, plasticity, porous media, fracture, fatigue, damage, delamination, viscosity, creep, shrinkage, etc); (ii) mechanics of structures (dynamics, vibration, seismic response, soil-structure interaction, fluid-structure interaction, response to blast and impact, response to fire, structural stability, buckling, collapse behaviour); (iii) numerical modelling and experimental testing (numerical methods, simulation techniques, multi-scale modelling, computational modelling, laboratory testing, field testing, experimental measurements); (iv) design in traditional engineering materials (steel, concrete, steel-concrete composite, aluminium, masonry, timber); (v) innovative concepts, sustainable engineering and special structures (nanostructures, adaptive structures, smart structures, composite structures, glass structures, bio-inspired structures, shells, membranes, space structures, lightweight structures, etc); (vi) the engineering process and life-cycle considerations (conceptualisation, planning, analysis, design, optimization, construction, assembly, manufacture, maintenance, monitoring, assessment, repair, strengthening, retrofitting, decommissioning). Two versions of the papers are available: full papers of length 6 pages are included in the e-book, while short papers of length 2 pages, intended to be concise but self-contained summaries of the full papers, are in the printed book. This work will be of interest to civil, structural, mechanical, marine and aerospace engineers, as well as planners and architects.

Artificial Neural Networks Formal Models and Their Applications ICANN 2005

Artificial Neural Networks  Formal Models and Their Applications     ICANN 2005 Book
Author : Wlodzislaw Duch,Erkki Oja,Slawomir Zadrozny
Publisher : Springer Science & Business Media
Release : 2005-08-31
ISBN : 3540287558
Language : En, Es, Fr & De

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Book Description :

The two volume set LNCS 3696 and LNCS 3697 constitutes the refereed proceedings of the 15th International Conference on Artificial Neural Networks, ICANN 2005, held in Warsaw, Poland in September 2005. The over 600 papers submitted to ICANN 2005 were thoroughly reviewed and carefully selected for presentation. The first volume includes 106 contributions related to Biological Inspirations; topics addressed are modeling the brain and cognitive functions, development of cognitive powers in embodied systems spiking neural networks, associative memory models, models of biological functions, projects in the area of neuroIT, evolutionary and other biological inspirations, self-organizing maps and their applications, computer vision, face recognition and detection, sound and speech recognition, bioinformatics, biomedical applications, and information- theoretic concepts in biomedical data analysis. The second volume contains 162 contributions related to Formal Models and their Applications and deals with new neural network models, supervised learning algorithms, ensemble-based learning, unsupervised learning, recurent neural networks, reinforcement learning, bayesian approaches to learning, learning theory, artificial neural networks for system modeling, decision making, optimalization and control, knowledge extraction from neural networks, temporal data analysis, prediction and forecasting, support vector machines and kernel-based methods, soft computing methods for data representation, analysis and processing, data fusion for industrial, medical and environmental applications, non-linear predictive models for speech processing, intelligent multimedia and semantics, applications to natural language processing, various applications, computational intelligence in games, and issues in hardware implementation.

Deep Learning By Example

Deep Learning By Example Book
Author : Ahmed Menshawy
Publisher : Packt Publishing Ltd
Release : 2018-02-28
ISBN : 178839576X
Language : En, Es, Fr & De

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Book Description :

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner Key Features Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Book Description Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. What you will learn Understand the fundamentals of deep learning and how it is different from machine learning Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning Increase the predictive power of your model using feature engineering Understand the basics of deep learning by solving a digit classification problem of MNIST Demonstrate face generation based on the CelebA database, a promising application of generative models Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation Who this book is for This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.

Meta Learning

Meta Learning Book
Author : Lan Zou
Publisher : Elsevier
Release : 2022-11-05
ISBN : 0323903703
Language : En, Es, Fr & De

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Book Description :

Deep neural networks (DNNs) with their dense and complex algorithms provide real possibilities for Artificial General Intelligence (AGI). Meta-learning with DNNs brings AGI much closer: artificial agents solving intelligent tasks that human beings can achieve, even transcending what they can achieve. Meta-Learning: Theory, Algorithms and Applications shows how meta-learning in combination with DNNs advances towards AGI. Meta-Learning: Theory, Algorithms and Applications explains the fundamentals of meta-learning by providing answers to these questions: What is meta-learning?; why do we need meta-learning?; how are self-improved meta-learning mechanisms heading for AGI ?; how can we use meta-learning in our approach to specific scenarios? The book presents the background of seven mainstream paradigms: meta-learning, few-shot learning, deep learning, transfer learning, machine learning, probabilistic modeling, and Bayesian inference. It then explains important state-of-the-art mechanisms and their variants for meta-learning, including memory-augmented neural networks, meta-networks, convolutional Siamese neural networks, matching networks, prototypical networks, relation networks, LSTM meta-learning, model-agnostic meta-learning, and the Reptile algorithm. The book takes a deep dive into nearly 200 state-of-the-art meta-learning algorithms from top tier conferences (e.g. NeurIPS, ICML, CVPR, ACL, ICLR, KDD). It systematically investigates 39 categories of tasks from 11 real-world application fields: Computer Vision, Natural Language Processing, Meta-Reinforcement Learning, Healthcare, Finance and Economy, Construction Materials, Graphic Neural Networks, Program Synthesis, Smart City, Recommended Systems, and Climate Science. Each application field concludes by looking at future trends or by giving a summary of available resources. Meta-Learning: Theory, Algorithms and Applications is a great resource to understand the principles of meta-learning and to learn state-of-the-art meta-learning algorithms, giving the student, researcher and industry professional the ability to apply meta-learning for various novel applications. A comprehensive overview of state-of-the-art meta-learning techniques and methods associated with deep neural networks together with a broad range of application areas Coverage of nearly 200 state-of-the-art meta-learning algorithms, which are promoted by premier global AI conferences and journals, and 300 to 450 pieces of key research Systematic and detailed exploration of the most crucial state-of-the-art meta-learning algorithm mechanisms: model-based, metric-based, and optimization-based Provides solutions to the limitations of using deep learning and/or machine learning methods, particularly with small sample sizes and unlabeled data Gives an understanding of how meta-learning acts as a stepping stone to Artificial General Intelligence in 39 categories of tasks from 11 real-world application fields