Multi Faceted Deep Learning

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Multi-faceted Deep Learning

Jenny Benois-Pineau,Akka Zemmari
Multi faceted Deep Learning Book PDF

Author : Jenny Benois-Pineau,Akka Zemmari
Publisher : Springer Nature
Page : 321 pages
File Size : 47,6 Mb
Release : 2021-10-20
Category : Computers
ISBN : 9783030744786

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Multi-faceted Deep Learning by Jenny Benois-Pineau,Akka Zemmari Pdf

This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems. The fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are first summarized in this book, which offers a comprehensive preamble for further problem–oriented chapters. The most interesting and open problems of machine learning in the framework of Deep Learning are discussed in this book and solutions are proposed. This book illustrates how to implement the zero-shot learning with Deep Neural Network Classifiers, which require a large amount of training data. The lack of annotated training data naturally pushes the researchers to implement low supervision algorithms. Metric learning is a long-term research but in the framework of Deep Learning approaches, it gets freshness and originality. Fine-grained classification with a low inter-class variability is a difficult problem for any classification tasks. This book presents how it is solved, by using different modalities and attention mechanisms in 3D convolutional networks. Researchers focused on Machine Learning, Deep learning, Multimedia and Computer Vision will want to buy this book. Advanced level students studying computer science within these topic areas will also find this book useful.

Machine Learning and Deep Learning in Real-Time Applications

Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Machine Learning and Deep Learning in Real Time Applications Book PDF

Author : Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Publisher : IGI Global
Page : 344 pages
File Size : 43,6 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9781799830979

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Machine Learning and Deep Learning in Real-Time Applications by Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan Pdf

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Multifaceted approaches for Data Acquisition, Processing & Communication

Chinmay Chakraborty,Manisha Guduri,B Sandhya,K Shyamala
Multifaceted approaches for Data Acquisition Processing Communication Book PDF

Author : Chinmay Chakraborty,Manisha Guduri,B Sandhya,K Shyamala
Publisher : CRC Press
Page : 293 pages
File Size : 52,9 Mb
Release : 2024-06-24
Category : Computers
ISBN : 9781040017043

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Multifaceted approaches for Data Acquisition, Processing & Communication by Chinmay Chakraborty,Manisha Guduri,B Sandhya,K Shyamala Pdf

The objective of the conference is to bring to focus the recent technological advancements across all the stages of data analysis including acquisition, processing, and communication. Advancements in acquisition sensors along with improved storage and computational capabilities, have stimulated the progress in theoretical studies and state-of-the-art real-time applications involving large volumes of data. This compels researchers to investigate the new challenges encountered, where traditional approaches are incapable of dealing with large, complicated new forms of data.

Machine Learning and Knowledge Discovery in Databases. Research Track

Nuria Oliver,Fernando Pérez-Cruz,Stefan Kramer,Jesse Read,Jose A. Lozano
Machine Learning and Knowledge Discovery in Databases Research Track Book PDF

Author : Nuria Oliver,Fernando Pérez-Cruz,Stefan Kramer,Jesse Read,Jose A. Lozano
Publisher : Springer Nature
Page : 817 pages
File Size : 53,5 Mb
Release : 2021-09-09
Category : Computers
ISBN : 9783030865207

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Machine Learning and Knowledge Discovery in Databases. Research Track by Nuria Oliver,Fernando Pérez-Cruz,Stefan Kramer,Jesse Read,Jose A. Lozano Pdf

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.

Foundations of Deep Learning

Tapomoy Adhikari
Foundations of Deep Learning Book PDF

Author : Tapomoy Adhikari
Publisher : Tapomoy Adhikari
Page : 57 pages
File Size : 50,9 Mb
Release : 2023-09-04
Category : Education
ISBN : 9798864253359

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Foundations of Deep Learning by Tapomoy Adhikari Pdf

"Foundations of Deep Learning" offers an erudite exploration into the dynamic landscape of artificial intelligence (AI) and deep learning, authored by Tapomoy Adhikari, an autonomous researcher in the field of Computer Science and Engineering. This scholarly work provides a comprehensive resource suitable for individuals at various stages of expertise, ranging from neophytes to seasoned practitioners within the domain of neural networks. Commencing with an introductory exposition, the book elucidates fundamental principles integral to deep learning. Subsequently, it undertakes a rigorous examination of neural network architectures, elucidating their constituent elements, activation functions, and optimization methodologies. The discourse extends to encompass the intricate mechanisms of backpropagation, a cornerstone process in neural network training. Further chapters delve deeply into Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), elucidating their pivotal roles across diverse applications such as computer vision and natural language processing. Noteworthy concepts explored include Generative Adversarial Networks (GANs), Attention Mechanisms, and Transfer Learning, furnishing readers with a comprehensive toolkit to address real-world challenges. In light of burgeoning ethical concerns within the AI landscape, the book offers nuanced insights into ethical considerations pertinent to deep learning. Emphasis is placed on responsible AI model development and its societal implications. The discourse extends to encompass the domain of Natural Language Processing (NLP) integrated with deep learning, elucidating concepts such as word embeddings and sequence-to-sequence models, alongside the transformative potential of attention mechanisms. Deep Reinforcement Learning, a pivotal paradigm underpinning gaming AI and autonomous systems, undergoes meticulous scrutiny, equipping readers with the requisite knowledge to navigate this burgeoning field. As the narrative culminates, readers are prompted to contemplate the future trajectory of deep learning, exploring themes such as neuro-symbolic integration, the potential impact of quantum computing, and the ethical imperatives guiding AI development. "Foundations of Deep Learning" transcends mere instructional discourse, serving as a scholarly compendium elucidating the inner workings of AI architectures shaping contemporary society. Augmented with code snippets, diagrams, and illustrative case studies, this academic endeavor facilitates a practical and accessible understanding of complex concepts. Irrespective of readers' academic or professional affiliations, be it as students, researchers, or engineers, this scholarly treatise equips them with the requisite knowledge and methodologies to navigate the ever-evolving landscape of neural networks.

Proceedings of International Joint Conference on Computational Intelligence

Mohammad Shorif Uddin,Jagdish Chand Bansal
Proceedings of International Joint Conference on Computational Intelligence Book PDF

Author : Mohammad Shorif Uddin,Jagdish Chand Bansal
Publisher : Springer Nature
Page : 642 pages
File Size : 50,9 Mb
Release : 2020-05-22
Category : Technology & Engineering
ISBN : 9789811536076

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Proceedings of International Joint Conference on Computational Intelligence by Mohammad Shorif Uddin,Jagdish Chand Bansal Pdf

This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2019), held at the University of Liberal Arts Bangladesh (ULAB), Dhaka, on 25–26 October 2019 and jointly organized by the University of Liberal Arts Bangladesh (ULAB), Bangladesh; Jahangirnagar University (JU), Bangladesh; and South Asian University (SAU), India. These proceedings present novel contributions in the areas of computational intelligence, and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

Artificial Neural Networks and Machine Learning – ICANN 2023

Lazaros Iliadis,Antonios Papaleonidas,Plamen Angelov,Chrisina Jayne
Artificial Neural Networks and Machine Learning ICANN 2023 Book PDF

Author : Lazaros Iliadis,Antonios Papaleonidas,Plamen Angelov,Chrisina Jayne
Publisher : Springer Nature
Page : 621 pages
File Size : 40,8 Mb
Release : 2023-09-21
Category : Computers
ISBN : 9783031442230

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Artificial Neural Networks and Machine Learning – ICANN 2023 by Lazaros Iliadis,Antonios Papaleonidas,Plamen Angelov,Chrisina Jayne Pdf

The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.

Machine Learning and Knowledge Discovery in Databases

Frank Hutter,Kristian Kersting,Jefrey Lijffijt,Isabel Valera
Machine Learning and Knowledge Discovery in Databases Book PDF

Author : Frank Hutter,Kristian Kersting,Jefrey Lijffijt,Isabel Valera
Publisher : Springer Nature
Page : 783 pages
File Size : 47,8 Mb
Release : 2021-02-24
Category : Computers
ISBN : 9783030676643

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Machine Learning and Knowledge Discovery in Databases by Frank Hutter,Kristian Kersting,Jefrey Lijffijt,Isabel Valera Pdf

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.

Synthetic Data for Deep Learning

Sergey I. Nikolenko
Synthetic Data for Deep Learning Book PDF

Author : Sergey I. Nikolenko
Publisher : Springer Nature
Page : 348 pages
File Size : 43,7 Mb
Release : 2021-06-26
Category : Computers
ISBN : 9783030751784

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Synthetic Data for Deep Learning by Sergey I. Nikolenko Pdf

This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine learning as a discipline would not be possible without the inner workings of optimization at hand. The book includes the necessary sinews of optimization though the crux of the discussion centers on the increasingly popular tool for training deep learning models, namely synthetic data. It is expected that the field of synthetic data will undergo exponential growth in the near future. This book serves as a comprehensive survey of the field. In the simplest case, synthetic data refers to computer-generated graphics used to train computer vision models. There are many more facets of synthetic data to consider. In the section on basic computer vision, the book discusses fundamental computer vision problems, both low-level (e.g., optical flow estimation) and high-level (e.g., object detection and semantic segmentation), synthetic environments and datasets for outdoor and urban scenes (autonomous driving), indoor scenes (indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision (in neural programming, bioinformatics, NLP, and more). It also surveys the work on improving synthetic data development and alternative ways to produce it such as GANs. The book introduces and reviews several different approaches to synthetic data in various domains of machine learning, most notably the following fields: domain adaptation for making synthetic data more realistic and/or adapting the models to be trained on synthetic data and differential privacy for generating synthetic data with privacy guarantees. This discussion is accompanied by an introduction into generative adversarial networks (GAN) and an introduction to differential privacy.

Intelligent Systems and Applications

W.C.-C. Chu,H.-C. Chao,S.J.-H. Yang
Intelligent Systems and Applications Book PDF

Author : W.C.-C. Chu,H.-C. Chao,S.J.-H. Yang
Publisher : IOS Press
Page : 2244 pages
File Size : 44,9 Mb
Release : 2015-04-14
Category : Computers
ISBN : 9781614994848

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Intelligent Systems and Applications by W.C.-C. Chu,H.-C. Chao,S.J.-H. Yang Pdf

This book presents the proceedings of the International Computer Symposium 2014 (ICS 2014), held at Tunghai University, Taichung, Taiwan in December. ICS is a biennial symposium founded in 1973 and offers a platform for researchers, educators and professionals to exchange their discoveries and practices, to share research experiences and to discuss potential new trends in the ICT industry. Topics covered in the ICS 2014 workshops include: algorithms and computation theory; artificial intelligence and fuzzy systems; computer architecture, embedded systems, SoC and VLSI/EDA; cryptography and information security; databases, data mining, big data and information retrieval; mobile computing, wireless communications and vehicular technologies; software engineering and programming languages; healthcare and bioinformatics, among others. There was also a workshop on information technology innovation, industrial application and the Internet of Things. ICS is one of Taiwan's most prestigious international IT symposiums, and this book will be of interest to all those involved in the world of information technology.

Deep Learning for Image Processing Applications

D.J. Hemanth,V. Vieira Estrela
Deep Learning for Image Processing Applications Book PDF

Author : D.J. Hemanth,V. Vieira Estrela
Publisher : IOS Press
Page : 284 pages
File Size : 49,6 Mb
Release : 2017-12
Category : Computers
ISBN : 9781614998228

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Deep Learning for Image Processing Applications by D.J. Hemanth,V. Vieira Estrela Pdf

Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, ‘Deep Learning for Image Processing Applications’, is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques.

Deep Learning for Computer Vision

Rajalingappaa Shanmugamani
Deep Learning for Computer Vision Book PDF

Author : Rajalingappaa Shanmugamani
Publisher : Packt Publishing Ltd
Page : 304 pages
File Size : 47,6 Mb
Release : 2018-01-23
Category : Computers
ISBN : 9781788293358

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Deep Learning for Computer Vision by Rajalingappaa Shanmugamani Pdf

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks Key Features Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more Includes tips on optimizing and improving the performance of your models under various constraints Book Description Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. What you will learn Set up an environment for deep learning with Python, TensorFlow, and Keras Define and train a model for image and video classification Use features from a pre-trained Convolutional Neural Network model for image retrieval Understand and implement object detection using the real-world Pedestrian Detection scenario Learn about various problems in image captioning and how to overcome them by training images and text together Implement similarity matching and train a model for face recognition Understand the concept of generative models and use them for image generation Deploy your deep learning models and optimize them for high performance Who this book is for This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book.

Artificial Intelligence Ethics and International Law

Abhivardhan
Artificial Intelligence Ethics and International Law Book PDF

Author : Abhivardhan
Publisher : BPB Publications
Page : 178 pages
File Size : 51,6 Mb
Release : 2023-12-01
Category : Computers
ISBN : 9789355516220

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Artificial Intelligence Ethics and International Law by Abhivardhan Pdf

Unveiling the future: Navigating AI's Intricate Intersection with International Law – A Journey Beyond Hype and Governance KEY FEATURES ● Comprehensive overview of AI ethics and international law. ● Exploration of pragmatic approaches to AI governance. ● Navigation of global legal dynamics. ● Soft law recommendations for responsible AI development. DESCRIPTION Dive into the dynamic realm of AI governance with this groundbreaking book. Offering cutting-edge insights, it explores the intricate intersection of artificial intelligence and international law. Readers gain invaluable perspectives on navigating the evolving AI landscape, understanding global legal dynamics, and delving into the nuances of responsible AI governance. Packed with pragmatic approaches, the book is an essential guide for professionals, policymakers, and scholars seeking a comprehensive understanding of the multifaceted challenges and opportunities presented by AI in the global legal arena. The book begins by examining the fundamental concepts of AI ethics and its recognition within international law. It then delves into the challenges of governing AI in a rapidly evolving technological landscape, highlighting the need for pragmatic and flexible approaches to AI regulation. Subsequent chapters explore the diverse perspectives on AI classification and recognition, from legal visibility frameworks to the ISAIL Classifications of Artificial Intelligence. The book also examines the far-reaching implications of Artificial General Intelligence (AGI) and digital colonialism, addressing the ethical dilemmas and potential dangers of these emerging technologies. In conclusion, the book proposes a path toward self-regulation and offers soft law recommendations to guide the responsible development and deployment of AI. It emphasizes the importance of international cooperation and collaboration in addressing the ethical and legal challenges posed by AI, ensuring that AI's transformative power is harnessed for the benefit of all humanity. WHAT YOU WILL LEARN ● Understand AI's impact on global legal frameworks. ● Navigate complexities of AI governance and responsible practices. ● Explore innovative AI applications and economic dimensions. ● Grasp legal visibility, privacy doctrines, and classification methods. ● Assess the evolution from Narrow AI to AGI and digital colonialism. ● Gain insights into self-regulation and the future of AI. WHO THIS BOOK IS FOR This book is tailored for professionals, policymakers, and scholars seeking a comprehensive understanding of AI's intersection with international law. While no specific prerequisites are necessary, a foundational awareness of AI concepts and legal frameworks will enhance the reader's engagement with the material. TABLE OF CONTENTS SECTION 1: Introduction 1. Artificial Intelligence and International Law SECTION 2: Technology Governance 2. Pragmatism in Governing AI 3. The Innovation and Economics of AI SECTION 3: Classification and Recognition of Artificial Intelligence 4. Legal Visibility 5. The Privacy Doctrine 6. The ISAIL Classifications of Artificial Intelligence SECTION 4: Artificial Intelligence in a Multi-polar World 7. AGI and Digital Colonialism 8. Self-Regulating the Future of AI

Machine Learning with Quantum Computers

Maria Schuld,Francesco Petruccione
Machine Learning with Quantum Computers Book PDF

Author : Maria Schuld,Francesco Petruccione
Publisher : Springer Nature
Page : 321 pages
File Size : 50,6 Mb
Release : 2021-10-17
Category : Science
ISBN : 9783030830984

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Machine Learning with Quantum Computers by Maria Schuld,Francesco Petruccione Pdf

This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.

Handbook of Research on Emerging Trends and Applications of Machine Learning

Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Handbook of Research on Emerging Trends and Applications of Machine Learning Book PDF

Author : Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Publisher : IGI Global
Page : 674 pages
File Size : 44,8 Mb
Release : 2019-12-13
Category : Computers
ISBN : 9781522596455

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Handbook of Research on Emerging Trends and Applications of Machine Learning by Solanki, Arun,Kumar, Sandeep,Nayyar, Anand Pdf

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.