Principles Of Catastrophic Forgetting For Continual Semantic Segmentation In Automated Driving
DOWNLOAD
Download Principles Of Catastrophic Forgetting For Continual Semantic Segmentation In Automated Driving PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Principles Of Catastrophic Forgetting For Continual Semantic Segmentation In Automated Driving book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Principles Of Catastrophic Forgetting For Continual Semantic Segmentation In Automated Driving
DOWNLOAD
Author : Kalb, Tobias Michael
language : en
Publisher: KIT Scientific Publishing
Release Date : 2024-10-21
Principles Of Catastrophic Forgetting For Continual Semantic Segmentation In Automated Driving written by Kalb, Tobias Michael and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-21 with categories.
Deep learning excels at extracting complex patterns but faces catastrophic forgetting when fine-tuned on new data. This book investigates how class- and domain-incremental learning affect neural networks for automated driving, identifying semantic shifts and feature changes as key factors. Tools for quantitatively measuring forgetting are selected and used to show how strategies like image augmentation, pretraining, and architectural adaptations mitigate catastrophic forgetting.
Trustworthy Distributed Usage Control Enforcement In Heterogeneous Trusted Computing Environments
DOWNLOAD
Author : Wagner, Paul Georg
language : en
Publisher: KIT Scientific Publishing
Release Date : 2025-01-17
Trustworthy Distributed Usage Control Enforcement In Heterogeneous Trusted Computing Environments written by Wagner, Paul Georg and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-17 with categories.
Distributed usage control allows to regulate the use of data even after sharing. However, existing solutions are susceptible to manipulation by dishonest data receivers. This work investigates the use of trusted computing to achieve a trustworthy usage control enforcement process. For this, a suitable system architecture and several remote attestation protocols are designed and implemented. The resulting usage control framework is evaluated using a smart manufacturing application scenario.
Advances In Brain Inspired Cognitive Systems
DOWNLOAD
Author : Amir Hussain
language : en
Publisher: Springer Nature
Release Date : 2025-03-10
Advances In Brain Inspired Cognitive Systems written by Amir Hussain and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-10 with Computers categories.
The two-volume set LNAI 15497 and LNAI 15498 constitutes the refereed proceedings of the 14th International Conference on Brain Inspired Cognitive Systems, BICS 2024, held in Hefei, China, during December 6–8, 2024. The 56 full papers presented in these two volumes were carefully reviewed and selected from 124 submissions. These papers deal with various aspects of brain inspired cognitive systems, focusing on latest advancements in brain-inspired computing; artificial intelligence; and cognitive systems.
Datensouver Nit T F R Betroffene Ber Pers Nliche Medizinische Daten Durch Technische Umsetzung Einer Datenschutzgerechten Forschungsplattform
DOWNLOAD
Author : Appenzeller, Arno
language : de
Publisher: KIT Scientific Publishing
Release Date : 2024-12-03
Datensouver Nit T F R Betroffene Ber Pers Nliche Medizinische Daten Durch Technische Umsetzung Einer Datenschutzgerechten Forschungsplattform written by Appenzeller, Arno and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with categories.
Die Digitalisierung im Gesundheitswesen schreitet mehr und mehr voran. Dies führt zu einer Zunahme an Daten, die für die sekundär Nutzung wie Forschung verfügbar sind. Aufgrund von Regulation existiert ein Spannungsfeld zwischen Forschungsnutzung und Datenschutz Im Rahmen dieser Dissertation werden Verfahren vorgestellt, die eine datenschutzfreundliche Forschungsnutzung von Daten durch Einwilligungsmanagement und Privatsphäre wahrende Technologien ermöglichen. - Digitalization in the healthcare sector is progressing more and more. This is leading to an increase in data that is available for secondary uses such as research. Due to regulation, there is a tension between research use and data protection This dissertation presents methods that enable data protection-friendly research use of data through consent management and privacy-preserving technologies.
General Video Game Artificial Intelligence
DOWNLOAD
Author : Diego Pérez Liébana
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2019-10-09
General Video Game Artificial Intelligence written by Diego Pérez Liébana and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-09 with Computers categories.
Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.
Federated Learning
DOWNLOAD
Author : Qiang Yang
language : en
Publisher: Springer Nature
Release Date : 2020-11-25
Federated Learning written by Qiang Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Computers categories.
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
Efficient Processing Of Deep Neural Networks
DOWNLOAD
Author : Vivienne Sze
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2020-06-24
Efficient Processing Of Deep Neural Networks written by Vivienne Sze and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-24 with Computers categories.
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of the DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as a formalization and organization of key concepts from contemporary works that provides insights that may spark new ideas.
Deep Learning
DOWNLOAD
Author : Ian Goodfellow
language : en
Publisher: MIT Press
Release Date : 2016-11-10
Deep Learning written by Ian Goodfellow and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-10 with Computers categories.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Neural Approaches To Conversational Ai Question Answering Task Oriented Dialogues And Social Chatbots
DOWNLOAD
Author : Jianfeng Gao
language : en
Publisher: Foundations and Trends(r) in I
Release Date : 2019-02-21
Neural Approaches To Conversational Ai Question Answering Task Oriented Dialogues And Social Chatbots written by Jianfeng Gao and has been published by Foundations and Trends(r) in I this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-21 with Computers categories.
This monograph is the first survey of neural approaches to conversational AI that targets Natural Language Processing and Information Retrieval audiences. It provides a comprehensive survey of the neural approaches to conversational AI that have been developed in the last few years, covering QA, task-oriented and social bots with a unified view of optimal decision making.The authors draw connections between modern neural approaches and traditional approaches, allowing readers to better understand why and how the research has evolved and to shed light on how they can move forward. They also present state-of-the-art approaches to training dialogue agents using both supervised and reinforcement learning. Finally, the authors sketch out the landscape of conversational systems developed in the research community and released in industry, demonstrating via case studies the progress that has been made and the challenges that are still being faced.Neural Approaches to Conversational AI is a valuable resource for students, researchers, and software developers. It provides a unified view, as well as a detailed presentation of the important ideas and insights needed to understand and create modern dialogue agents that will be instrumental to making world knowledge and services accessible to millions of users in ways that seem natural and intuitive.