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Artificial neural networks with Java : Tools for Building Neural Network Applications
Covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. You will learn: Use Java for the development of neural network applications / Prepare data for many different tasks / Carry out some unusual neural network processing / Use a neural network to process non-continuous functions / Develop a program that recognizes handwritten digits
Artificial neural networks : Formal Models and Their Applications – ICANN 2005 ; 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II
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.
Artificial Intelligence with Python
Introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.
Artificial intelligence in education ; 21st International conference, AIED 2020, Ifrane, Morocco, July 6–10, 2020, Proceedings, Part II
This two-volume set LNAI 12163 and 12164 constitutes the refereed proceedings of the 21th International Conference on Artificial Intelligence in Education, AIED 2020, held in Ifrane, Morocco, in July 2020.* The 49 full papers presented together with 66 short, 4 industry & innovation, 4 doctoral consortium, and 4 workshop papers were carefully reviewed and selected from 214 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
Artificial intelligence in education ; 21st International conference, AIED 2020, Ifrane, Morocco, July 6–10, 2020, Proceedings, Part I
This two-volume set LNAI 12163 and 12164 constitutes the refereed proceedings of the 21th International Conference on Artificial Intelligence in Education, AIED 2020, held in Ifrane, Morocco, in July 2020.* The 49 full papers presented together with 66 short, 4 industry & innovation, 4 doctoral consortium, and 4 workshop papers were carefully reviewed and selected from 214 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
Artificial intelligence for multimedia signal processing
Artificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three years to improve image, video, speech, and other data compression efficiency in areas related to MPEG media processing technology. Additionally, technologies such as media creation, processing, editing, and creating scenarios are very important areas of research in multimedia processing and engineering. This book contains a collection of some topics broadly across advanced computational intelligence algorithms and technologies for emerging multimedia signal processing as: Computer vision field, speech/sound/text processing, and content analysis/information mining.
Artificial intelligence for customer relationship management : Solving customer problems
This book describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer.
Artificial intelligence for customer relationship management : Keeping customers informed
Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals.
Artificial intelligence applications and innovations II; IFIP TC12 and WG12.5 ; 2nd IFIP conference on artificial intelligence applications and innovations (AIAI-2005), Sept. 7-9, 2005, Beijing, China
Artificial Intelligence is one of the oldest and most exciting subfields of computing, covnering such areas as intelligent robotics, intelligent planning and scheduling, model-based reasoning, fault diagnosis, natural language processing, maching translation, knowledge representation and reasoning, knowledge-based systems, knowledge engineering, intelligent agents, machine learning, neural nets, genetic algorithms and knowledge management. The papers in this volume comprise the refereed proceedings of the Second International Conference on Artificial Intelligence Applications and Innovations,held in Beijing, China in 2005.
Artificial intelligence and soft computing - ICAISC 2008 ; 9th International Conference Zakopane, Poland, June 22-26, 2008 Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008, held in Zakopane, Poland, in June 2008.
Artificial intelligence : Methodology, systems, and applications ; 12th International Conference, AIMSA 2006, Varna, Bulgaria, September 12-15, 2006, Proceedings
This book constitutes the refereed proceedings of the 12th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2006. The 28 revised full papers presented together with the abstracts of 2 invited lectures were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on agents, constraints and optimization, user concerns, decision support, models and ontologies, machine learning, ontology manipulation, natural language processing, and applications.
Artificial intelligence : Methodology, systems, and applications ; 10th International Conference, AIMSA 2002, Varna, Bulgaria, September 4-6, 2002. Proceedings
The AIMSA conference series was frst conceived in 1984 as a gathering of AI researchers and students from Eastern and Central Europe.Sincethenthecon- rence has followed a biennial schedule of meetings in Bulgaria, attracting parti- pantsfrom awidergeographicalarea.The AIMSA organizers are delighted to present you with another exciting program, coveringmostareasof Artifcial Intelligence.Inkeepingwithitsm- sion to inform the research community and excite the commercial sector, AIMSA presents this year two invited contributions from world-leading European rese- chersworkingoncutting-edgeAIresearch: Prof.CaroleGoble, ontheSemantic Web.
Artificial intelligence : A modern approach ; global ed.
Explores the full breadth and depth of the field of artificial intelligence (AI). The 4th edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multi agent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI
Argumentation in multi-agent systems ; 4th International Workshop, ArgMAS 2007, Honolulu, HI, USA, May 15, 2007, revised selected and invited papers
This volume presents the latest developments in the growing area of research at the interface of argumentation theory and multiagent systems. Argumentation provides tools for designing, implementing and analyzing sophisticated forms of interaction among rational agents.
Architecture of advanced numerical analysis systems: designing a scientific computing system using ocaml
Applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language.
Architecture description languages ; IFIP TC-2 workshop on architecture description languages (WADL), World Computer Congress, Aug. 22-27, 2004, Toulouse, France
These proceedings record the papers presented at the Workshop onArchitecture Description Languages held in the city of Toulouse in thesouth of France.The aim of an ADL (Architecture Description Language) is to formallydescribe software and hardware architectures. Usually, an ADL describescomponents, their interfaces, their structures, their interactions (structureof data flow and control flow) and the mappings to hardware systems. Amajor goal of such descriptions is to allow analysis with respect to severalaspects like timing, safety, reliability, ...
Architecting dependable systems IV
As software systems become ubiquitous, the issues of dependability become more and more crucial. Given that solutions to these issues must be considered from the very beginning of the design process, it is reasonable that dependability is addressed at the architectural level. It also contains sections on architectural description languages, architectural components and patterns, architecting distributed systems, and architectural assurances for dependability.
Arabic and Chinese Handwriting Recognition ; SACH 2006 Summit College Park, MD, USA, September 27-28, 2006 Selected Papers
Cheriet provides an overview of the problems of Arabic recognition and how systems can use natural language processing techniques to correct errors in lexicon-based systems.
Arabic AI-generated adverts = إعلانات عربية مولدة بالذكاء الاصطناعي
In the ever-evolving landscape of digital marketing, our groundbreaking platform emerges, harnessing the power of artificial intelligence to revolutionize the creation of marketing campaigns. This innovative solution seamlessly combines neural networks, natural language generation, and multimedia processing capabilities to generate comprehensive and personalized marketing assets from a single product image. At its core, the platform leverages deep learning models that analyze the visual characteristics of the uploaded product image and identifies key features and attributes to define the product category, this enables the generation of compelling and persuasive marketing content tailored to the specific product. The platform's multi-faceted approach encompasses three distinct components: text generation, poster creation, and video advertisement production. Utilizing advanced natural language generation techniques, it crafts engaging marketing text that captures the essence and unique selling points of the product. Simultaneously, its image processing capabilities produce visually stunning promotional posters that blend the product image with eye-catching graphics and typography. along with creating captivating video advertisements optimized for social media and online advertising campaigns.
Applied Deep Learning with TensorFlow 2 : Learn to Implement Advanced Deep Learning Techniques with Python
Focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects. This book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks. All the code presented in the book will be available in the form of Jupyter notebooks which would allow you to try out all examples and extend them in interesting ways. A companion online book is available with the complete code for all examples discussed in the book and additional material more related to TensorFlow and Keras. All the code will be available in Jupyter notebook format and can be opened directly in Google Colab (no need to install anything locally) or downloaded on your own machine and tested locally. You will: Understand the fundamental concepts of how neural networks work / Learn the fundamental ideas behind autoencoders and generative adversarial networks / Be able to try all the examples with complete code examples that you can expand for your own projects / Have available a complete online companion book with examples and tutorials.
