الصفحة 10
الصفحة 10
Artificial Intelligence : Applications and innovations
It's about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Provides insight into prospective research and application areas related to industry and technology / Discusses industry- based inputs on success stories of technology adoption / Discusses technology applications from a research perspective in the field of AI / Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning
Architecture of computing systems ; 34th International Conference, ARCS 2021, Virtual Event, June 7–8, 2021, Proceedings
This book constitutes the proceedings of the 34th International Conference on Architecture of Computing Systems, ARCS 2021, held virtually in July 2021. The 12 full papers in this volume were carefully reviewed and selected from 24 submissions. 2 workshop papers (VEFRE) are also included. ARCS has always been a conference attracting leading-edge research outcomes in Computer Architecture and Operating Systems, including a wide spectrum of topics ranging from fully integrated, self-powered embedded systems up to high-performance computing systems. It also provides a platform covering newly emerging and cross-cutting topics, such as autonomous and ubiquitous systems, reconfigurable computing and acceleration, neural networks and artificial intelligence. The selected papers cover a variety of topics from the ARCS core domains, including heterogeneous computing, memory optimizations, and organic computing.
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.
Applications of computational intelligence
Computational intelligence (CI) is the theory, design, application, and development of biologically and linguistically motivated computational paradigms. Traditionally, the three main pillars of CI have been neural networks, fuzzy systems, and evolutionary computation. However, in time, many nature-inspired computing paradigms have evolved. Thus, CI is an evolving field, and, at present, in addition to the three main constituents, it encompasses computing paradigms such as ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a major role in developing successful intelligent systems, including games and cognitive developmental systems.
Application of power electronics converters in smart grids and renewable energy systems
Focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller.
An Intuitive Exploration of Artificial Intelligence : Theory and Applications of Deep Learning
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future.
Algorithms for a New World : When Big Data and Mathematical Models Meet
Algorithms, artificial neural networks, and machine learning help us discover the opportunities and pitfalls of a world governed by mathematics and artificial intelligence.
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
AI based Robot Safe Learning and Control
This book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning.
AI and UX : Why artificial intelligence needs user experience
Great effort has been put forth to continuously make AI “smarter.” But, will smarter always equal more successful AI? It is not just about getting a product to market, but about getting the product into a user’s hands in a form that will be embraced. This demands examining the product from the perspective of the user. Authors Gavin Lew and Robert Schumacher have written AI and UX to examine just how product managers and designers can best strike this balance. From exploring the history of the parallel journeys of AI and UX, to investigating past product examples and failures, to practical expert knowledge on how to best execute a positive user experience, AI and UX examines all angles of how AI can best be developed within a UX framework.
AI 2020 : Advances in artificial intelligence ; 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29–30, 2020, Proceedings
Constitutes the proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence, AI 2020, held in Canberra, ACT, Australia, in November 2020.* The 36 full papers presented in this volume were carefully reviewed and selected from 57 submissions. The paper were organized in topical sections named: applications; evolutionary computation; fairness and ethics; games and swarms; and machine learning.
AI 2007: Advances in artificial intelligence ; 20th Australian Joint Conference on Artificial Intelligence, Gold Coast, Australia, December 2-6, 2007, Proceedings
The book is organized in topical sections on machine learning, neural networks, evolutionary computing, constraint satisfaction, satisfiability, automated reasoning, knowledge discovery, robotics, social intelligence, ontologies and semanti.
AI 2006 : Advances in artificial intelligence ; 19th Australian Joint Conference on Artificial Intelligence, Hobart, Australia, December 4-8, 2006, Proceedings
This volume contains the proceedings of the 19th Australian Joint Conference on Artificial Intelligence (AI 2006) held at Hobart, Australia. AI 2006 received a record number of submissions, a total of 689 submissions from 35 countries. The papers in this volume give an indication of recent advances in artificial int- ligence. The topics covered include Machine Learning, Robotics, AI Applications, Planning, Agents, Data Mining and Knowledge Discovery, Cognition and User Interface, Vision and Image Processing, Information Retrieval and Search, AI in the Web, Knowledge Representation, Knowledge-Based Systems, and Neural Networks.
AI 2005 : Advances in artificial intelligence ; 18th Australian joint conference on artificial intelligence, Sydney, Australia, December 5-9, 2005, proceedings
The 18th Australian Joint Conference on Artificial Intelligence (AI 2005) was held at the University of Technology, Sydney (UTS), Sydney, Australia from 5 to 9 December 2005. AI 2005 attracted a historical record number of submissions, a total of 535 papers. This volume of the proceedings contains the abstracts of three keynote speeches and all the full and short papers. The full papers were categorized into three broad sections, namely: AI foundations and technologies, computational intelligence, and AI in specialized domains. AI 2005 also hosted several tutorials and workshops, providing an interacting mode for specialists and scholars from Australia and other countries.
Advances in optical fiber communications
Given the increasing importance of a globally interconnected world, driven by modern digital services and the need for fast and reliable access to digital resources, communication networks are one of the key infrastructures in today’s society. In this scenario, fiber optics and optical devices play a leading role, as they allow for unprecedented growth in our capacity to cope with the ever-increasing traffic demand. Optical transmission solutions range from high-speed networks based on coherent detection and advanced modulation formats for long-haul-level communications, to networks still relying on traditional intensity modulation and direct detection receivers for short-reach communications, down to intra-data center scenarios.
Advances in neural networks - ISNN 2008 ; 5th International symposium on neural networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part II
The two volume set LNCS 5263/5264 constitutes the refereed proceedings of the 5th International Symposium on Neural Networks, ISNN 2008, held in Beijing, China in September 2008.
Advances in Neural Networks - ISNN 2008 ; 5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I
The two volume set LNCS 5263/5264 constitutes the refereed proceedings of the 5th International Symposium on Neural Networks, ISNN 2008, held in Beijing, China in September 2008.
Advances in neural networks -- ISNN 2007 ; 4th International symposium on neutral networks, ISNN 2007 Nanjing, China, June 3-7, 2007. Proceedings, Part II
An eural network is an information processing structure inspired by biological nervous systems, such as the brain. It consists of a large number of highly int- connected processing elements, called neurons. It has the capability of learning from example.
Advances in Neural Networks -- ISNN 2007 ; 4th International Symposium on Neutral Networks, ISNN 2007 Nanjing, China, June 3-7, 2007. Proceedings, Part I
An eural network is an information processing structure inspired by biological nervous systems, such as the brain. It consists of a large number of highly int- connected processing elements, called neurons. It has the capability of learning from example.
