Описание: This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and edical image processing and analysis. The book is directed to the Ph.D.
Описание: This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D.
Автор: Yves Demazeau; Frank Dignum; Juan Manuel Corchado Название: Advances in Practical Applications of Agents and Multiagent Systems ISBN: 364212383X ISBN-13(EAN): 9783642123832 Издательство: Springer Рейтинг: Цена: 34799.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an international yearly stage to present, to discuss, and to disseminate the latest advances and the most important outcomes related to real-world applications. This volume presents the papers that have been accepted for the 2010 edition.
Описание: This book constitutes the refereed proceedings of the 12th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2014, held in Salamanca, Spain, in June 2014.
Simulating Sustainability: Guiding Principles to Ensure Policy Impact.- Papers Evaluating the Social Benefit of a Negotiation-Based Parking Allocation.- Load Management Through Agent Based Coordination of Flexible Electricity Consumers.- Agent-Based Distributed Analytical Search.- Distributed Belief Propagation in Multi-agent Environment.- Situated Artificial Institution to Support Advanced Regulation in the Field of Crisis Management.- Trusting Information Sources Through Their Categories.- AGADE Using Personal Preferences and World Knowledge to Model Agent Behaviour.- Contextualize Agent Interactions by Combining Communication and Physical Dimensions in the Environment.- ''1-N'' Leader-Follower Formation Control of Multiple Agents Based on Bearing-Only Observation.- Echo State Networks for Feature Selection in Affective Computing.- Performance Investigation on Binary Particle Swarm Optimization for Global Optimization .- Contracts for Difference and Risk Management in Multi-agent Energy Markets.- Why Are Contemporary Political Revolutions Leaderless? An Agent-Based Explanation.- Time Machine: Projecting the Digital Assets onto the Future Simulation Environment.- From Goods to Traffic: First Steps Toward an Auction-Based Traffic Signal Controller.- Social Emotional Model.- AgentDrive: Towards an Agent-Based Coordination of Intelligent Cars.- Multi-agent Based Flexible Deployment of Context Management in Ambient Intelligence Applications.- Multi-agent Multi-model Simulation of Smart Grids in the MS4SG Project.- iaBastos: An Intelligent Marketplace for Agricultural Products.- TrafficGen: A Flexible Tool for Informing Agent-Based Traffic Simulations with Open Data.- Distributed Analytical Search.- Situated Regulation on a Crisis Management Collaboration Platform.- Demo Paper: AGADE Using Communities of Agents to Provide Realistic Feedback in Business Simulations.- BactoSim - An Individual-Based Simulation Environment for Bacterial Conjugation.- A Multimodal City Street and Entertainment Guide for Android Mobile Devices.- EXPLAIN_MAS: An Agent Behavior Explanation System.- A Fully Integrated Development Environment for Agent-Oriented Programming.- Can Social Media Substitute Revolutionary Leaders? An Agent-Based Demonstration.- Simulating the Optimization of Energy Consumption in Homes.- First Steps Toward an Auction-Based Traffic Signal Controller.-Addressing Long-Term Digital Preservation Through Computational Intelligence.- Representing Social Emotions in MAS.- Developing Agent-Based Driver Assistance Systems Using AgentDrive.- Demonstration of Realistic Multi-agent Scenario Generator for Electricity Markets Simulation.- Smart Grids Simulation with MECSYCO.
Описание: The application and validation of agent-based models.- Methods, and technologies in a number of key application areas.- In day life and real world, energy and networks, human and trust, markets and bids, models and tools, negotiation and conversation, scalability and resources.
Описание: This book constitutes the proceedings of the 16th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2018, held in Toledo, Spain, in June 2018. They deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, such as: energy and security;
Описание: This book constitutes the proceedings of the 17th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2019, held in ?vila, Spain, in June 2019.The 19 regular and 14 demo papers presented in this volume were carefully reviewed and selected from 55 submissions. They deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, including: Agronomy and Internet of Things, coordination and structure, finance and energy, function and autonomy, humans and societies, reasoning and optimization, traffic and routing.
Описание: This book constitutes the proceedings of the 18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020, held in L`Aquila, Italy, in October 2020. The 29 regular and 17 demo papers presented in this volume were carefully reviewed and selected from 64 submissions.
Описание: This book constitutes the proceedings of the 19th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2021, held in Salamanca, Spain, in October 2021. The 27 regular and 13 short papers presented in this volume were carefully reviewed and selected from 56 submissions.
Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms.
For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than the fully connected ANN (FCNN). You will implement a CNN in Python to give you a full understanding of the model.
After consolidating the basics, you will use TensorFlow to build a practical image-recognition model that you will deploy to a web server using Flask, making it accessible over the Internet. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads.
This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production.
What You Will Learn
Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using PythonFollow a deep learning project from conception to production using TensorFlowUse NumPy with Kivy to build cross-platform data science applications
Who This Book Is For
Data scientists, machine learning and deep learning engineers, software developers.
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