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الصفحة 34
Advanced Intelligent Computing Theories and Applications : With Aspects of Artificial Intelligence ; 3rd International Conference on Intelligent Computing, ICIC 2007, Qingdao, China, August 21-24, 2007, Proceedings
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring gether researchers and practitioners from both academia and industry to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications.
Advanced driver assistance system (ADAS)
The purpose of Advanced Driver Assistance Systems (ADAS) is to reduce or eliminate driver errors, and to enhance efficiency in traffic and transportation. Our project is a means and a great contribution to safe driving, and the user does not need to install sensors or hard tools to the vehicle, and through it, the cost can be reduced and maintenance cost can be eliminated. The images are processed and segmented to find different features in the image. Segmented images are used for identification and classification based on various machine learning algorithms and neural networks. The main focus of ADAS technologies is to contribute to factors such as safety management and automated, stress-free driving for the driver
Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms : A Practical Approach Using Python
Describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies.
Advanced data mining and applications ; Vol. 3584 ; 1st International Conference, ADMA 2005, Wuhan, China, July 22-24, 2005, Proceedings
This book constitutes the refereed proceedings of the First International Conference on Advanced Data Mining and Applications, ADMA 2005, held in Wuhan, China in July 2005. The 25 revised full papers and 75 revised short papers presented were carefully peer-reviewed and The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, text mining, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, security and privacy issues, spatial data mining, and streaming data mining.
Advanced artificial intelligence models and its applications
The field of artificial intelligence (AI) has undergone enormous expansion since its inception in the mid-20th century, as demonstrated by its application across an array of engineering and scientific challenges. Particularly in the last decade, AI has witnessed a significant breakthrough with the advent of deep learning, which has facilitated the employment of various AI models across a multitude of domains. This reprint features ten papers accepted for publication in the Special Issue titled "Advanced Artificial Intelligence Models and Their Applications," published in the MDPI Mathematics journal. These papers explore numerous facets of advanced artificial intelligence models and their applications, covering areas such as cybersecurity, image classification, logistics optimization, automatic music generation, human capital investment, writer recognition, remote sensing image indexing, target tracking, and more.
Advanced Algorithms and Data Structures
introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms
AdvancED ActionScript Components : Mastering the Flash Component Architecture
Macromedia's architecture is like a chest filled with precious jewels, and this book is quite simply the key to open it! One of the most important tools provided with Flash is the Macromedia Component Architecture: a framework of components written in ActionScript 2, based on established design patterns, that provides a wealth of functionality you can just bolt on to your Flash applications when desired. This can save you an enormous amount of time during application development and help you improve the quality of your code. What's more, the source code is included, so if you can't find the component you need within the component architecture, you can just modify existing components to create your own!
Advance Concepts of Image Processing and Pattern Recognition : Effective Solution for Global Challenges
Explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc.
Ad-Hoc, mobile, and wireless networks ; 6th International Conference, ADHOC-NOW 2007, Morelia, Mexico, September 24-26, 2007, Proceedings
The sixth international conference on AD-HOC NetwOrks and Wireless was held in the city of Morelia, Michoacan State, Mexico. It follows the tradition of a multidisciplinary research program on all aspects of ad hoc networks that aims to create a collaborative forum between mathematicians, computer scientists and engineers. Previous Ad-Hoc Networks and Wireless conferences were held.
Ad-hoc, Mobile and Wireless Networks ; 7th International Conference, ADHOC-NOW 2008 Sophia-Antipolis, France, September 10-12, 2008 Proceedings
This book constitutes the refereed proceedings of the 7th International Conference on Ad-Hoc, Mobile, and Wireless Networks, ADHOC-NOW 2008, held in Sophia-Antipolis, France, September 2008.
Adaptive Multimedial Retrieval : Retrieval, User, and Semantics ; 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007 Revised Selected Papers
This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Adaptive Multimedia Retrieval, AMR 2007, held in Paris, France, in July 2007.
Adaptive Multimedia Retrieval : User, Context, and Feedback ; 4th International Workshop, AMR 2006, Geneva, Switzerland, July, 27-28, 2006, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Adaptive Multimedia Retrieval, AMR 2006, held in Geneva, Switzerland in July 2006. this book provides a good and conclusive overview of the current research in the area of adaptive information retrieval.
Adaptive Motion of Animals and Machines
Apparently, the ability of animals and robots to adapt in a real world cannot be explained or realized by one single function in a control system and mechanism. That is, adaptation in motion is induced at every level from the central nervous system to the musculoskeletal system.Thus,weorganized the International Symposium on Adaptive Motion in Animals and Machines (AMAM) forscientist sandengineersconcerned with adaptation on various level stobebrought together todiscussprinciplesateachleveland to investigate principles governing total systems.
Adaptive Machine Learning Algorithms with Python : Solve Data Analytics and Machine Learing Problems on Edge Devices
Learn to use adaptive algorithms to solve real-world streaming data problems. This book covers a multitude of data processing challenges, ranging from the simple to the complex. At each step, you will gain insight into real-world use cases, find solutions, explore code used to solve these problems, and create new algorithms for your own use. You will: Apply adaptive algorithms to practical applications and examples / Understand the relevant data representation features and computational models for time-varying multi-dimensional data / Derive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real data / Speed up your algorithms and put them to use on real-world stationary and non-stationary data / Master the applications of adaptive algorithms on critical edge device computation applications
Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic time-series prediction, financial forecasting and data mining. The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution. When the learning process is organized according to these steps, performed together one after the other or separately, one may expect to discover models that generalize well.
Adaptive Autonomous Secure Cyber Systems
Establishes scientific foundations for adaptive autonomous cyber systems and ultimately brings about a more secure and reliable Internet. The recent advances in adaptive cyber defense (ACD) have developed a range of new ACD techniques and methodologies for reasoning in an adaptive environment.
Adaptive and natural computing algorithms ; Proceedings of the International Conference in Coimbra, Portugal, 2005
The ICANNGA series of Conferences has been organised since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scientific community and is a reference for established workers in this area.and this book about Proceedings of the International Conference in Coimbra, Portugal, 2005 including Topics Artificial Intelligence Simulation and Modeling / Mathematics of Computing / Computer Applications
Adaptive and Natural Computing Algorithms ; 8th International Conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007, Proceedings, Part I
Constitutes the refereed proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007, held in Warsaw, Poland, in April 2007. The 178 revised full papers presented were carefully reviewed and selected from a total of 474 submissions. The 94 papers of the first volume are organized in topical sections on evolutionary computation, genetic algorithms, particle swarm optimization, learning, optimization and games, fuzzy and rough systems, just as classification and clustering. The second volume contains 84 contributions related to neural networks, support vector machines, biomedical signal and image processing, biometrics, computer vision, as well as to control and robotics.
Adaptive agents and multi-agent systems III : Adaptation and multi-Agent learning ; 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems, Revised Selected Papers
This book contains selected and revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS).
Adaptive agents and multi-agent systems II : Adaptation and multi-agent learning
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
