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This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023. The 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: Theory and Methods; Scale Space, PDEs, Flow, Motion and Registration.

Research findings help in policy making for research establishment and funding agencies. It provides new avenues for the researchers to carry out further. The scholarly study of communication includes the growth of scholarly information, the relationships among research areas and disciplines, the information needs and uses of individual user groups, and the relationships among formal and informal methods of communication (Kumar, 2004).Quantitative analysis is the main tool in science by means of counting, measuring, comparing and analyzing the data.The publication of research results is enormous and complex.

Scale up your Windows containers seamlessly on AWS powered by field-proven expertise and best practices on Amazon ECS, EKS, and FargatePurchase of the print or Kindle book includes a free PDF eBookKey Features:Learn how to quickly deploy and automate end-to-end CV pipelines on AWSImplement design principles to mitigate bias and scale production of CV workloadsWork with code examples to master CV concepts using AWS AI/ML servicesBook Description:Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models.You'll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that'll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads.By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services.What You Will Learn:Apply CV across industries, including e-commerce, logistics, and mediaBuild custom image classifiers with Amazon Rekognition Custom LabelsCreate automated end-to-end CV workflows on AWSDetect product defects on edge devices using Amazon Lookout for VisionBuild, deploy, and monitor CV models using Amazon SageMakerDiscover best practices for designing and evaluating CV workloadsDevelop an AI governance strategy across the entire machine learning life cycleWho this book is for:If you are a machine learning engineer or data scientist looking to discover best practices and learn how to build comprehensive CV solutions on AWS, this book is for you. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. A solid understanding of machine learning concepts and the Python programming language will also be beneficial.

Explore Detectron2 using cutting-edge models and learn all about implementing future computer vision applications in custom domainsPurchase of the print or Kindle book includes a free PDF eBookKey Features:- Learn how to tackle common computer vision tasks in modern businesses with Detectron2- Leverage Detectron2 performance tuning techniques to control the model's finest details- Deploy Detectron2 models into production and develop Detectron2 models for mobile devicesBook Description:Computer vision is a crucial component of many modern businesses, including automobiles, robotics, and manufacturing, and its market is growing rapidly. This book helps you explore Detectron2, Facebook's next-gen library providing cutting-edge detection and segmentation algorithms. It's used in research and practical projects at Facebook to support computer vision tasks, and its models can be exported to TorchScript or ONNX for deployment.The book provides you with step-by-step guidance on using existing models in Detectron2 for computer vision tasks (object detection, instance segmentation, key-point detection, semantic detection, and panoptic segmentation). You'll get to grips with the theories and visualizations of Detectron2's architecture and learn how each module in Detectron2 works. As you advance, you'll build your practical skills by working on two real-life projects (preparing data, training models, fine-tuning models, and deployments) for object detection and instance segmentation tasks using Detectron2. Finally, you'll deploy Detectron2 models into production and develop Detectron2 applications for mobile devices.By the end of this deep learning book, you'll have gained sound theoretical knowledge and useful hands-on skills to help you solve advanced computer vision tasks using Detectron2.What You Will Learn:- Build computer vision applications using existing models in Detectron2- Grasp the concepts underlying Detectron2's architecture and components- Develop real-life projects for object detection and object segmentation using Detectron2- Improve model accuracy using Detectron2's performance-tuning techniques- Deploy Detectron2 models into server environments with ease- Develop and deploy Detectron2 models into browser and mobile environmentsWho this book is for:If you are a deep learning application developer, researcher, or software developer with some prior knowledge about deep learning, this book is for you to get started and develop deep learning models for computer vision applications. Even if you are an expert in computer vision and curious about the features of Detectron2, or you would like to learn some cutting-edge deep learning design patterns, you will find this book helpful. Some HTML, Android, and C++ programming skills are advantageous if you want to deploy computer vision applications using these platforms.Table of Contents- An Introduction to Detectron2 and Computer Vision Tasks- Developing Computer Vision Applications Using Existing Detectron2 Models- Data Preparation for Object Detection Applications- The Architecture of the Object Detection Model in Detectron2- Training Custom Object Detection Models- Inspecting Training Results and Fine-Tuning Detectron2's Solver- Fine-Tuning Object Detection Models- Image Data Augmentation Techniques- Applying Train-Time and Test-Time Image Augmentations- Training Instance Segmentation Models- Fine-Tuning Instance Segmentation Models- Deploying Detectron2 Models into Server Environments- Deploying Detectron2 models into Browsers and Mobile Environments

This textbook presents the theoretical foundations of machine learning along with its practical implementation in Python, to help a beginner learn and implement all aspects of the subject. It will be a vital resource for both students and professionals looking for a primer in data science and machine learning.

This book is your ultimate guide to understanding the revolutionary technology of Artificial Intelligence (AI). This book covers everything from the basics of AI to its profound impact on various industries, such as healthcare, transportation, banking, and entertainment. You will discover the endless possibilities of AI and how it is changing our lives for the better.The book begins with an introduction to AI and its significance in the modern world. You will learn about the various applications of AI, including speech recognition assistants, image recognition, and biometric data analysis. This will give you a comprehensive understanding of how AI is used in our daily lives and the different industries benefiting from its advancements.In the following chapters, you will delve deeper into the workings of AI, machine learning, deep learning, neural networks, and natural language generation. The book explains how these technologies function and how they are applied in real-life scenarios. You will also gain insights into the differences between human and machine intelligence, providing a holistic understanding of AI's capabilities and limitations.Whether you are a business decision-maker, an IT professional, or someone who is merely interested in the impact of AI on the world, this book is a must-read. With its easy-to-understand language and numerous examples, it empowers you to comprehend the complex technology of AI and be part of the conversation shaping our future.

This book presents the modern technological advancements and revolutions in the biomedical sector. Progress in the contemporary sensing, Internet of Things (IoT) and machine learning algorithms and architectures have introduced new approaches in the mobile healthcare. A continuous observation of patients with critical health situation is required. It allows monitoring of their health status during daily life activities such as during sports, walking and sleeping. It is realizable by intelligently hybridizing the modern IoT framework, wireless biomedical implants and cloud computing. Such solutions are currently under development and in testing phases by healthcare and governmental institutions, research laboratories and biomedical companies. The biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG), Electromyography (EMG), phonocardiogram (PCG), Chronic Obstructive Pulmonary (COP), Electrooculography (EoG), photoplethysmography (PPG), and image modalitiessuch as positron emission tomography (PET), magnetic resonance imaging (MRI) and computerized tomography (CT) are non-invasively acquired, measured, and processed via the biomedical sensors and gadgets. These signals and images represent the activities and conditions of human cardiovascular, neural, vision and cerebral systems. Multi-channel sensing of these signals and images with an appropriate granularity is required for an effective monitoring and diagnosis. It renders a big volume of data and its analysis is not feasible manually. Therefore, automated healthcare systems are in the process of evolution. These systems are mainly based on biomedical signal and image acquisition and sensing, preconditioning, features extraction and classification stages. The contemporary biomedical signal sensing, preconditioning, features extraction and intelligent machine and deep learning-based classification algorithms are described. Each chapter starts with the importance, problemstatement and motivation. A self-sufficient description is provided. Therefore, each chapter can be read independently. To the best of the editors¿ knowledge, this book is a comprehensive compilation on advances in non-invasive biomedical signal sensing and processing with machine and deep learning. We believe that theories, algorithms, realizations, applications, approaches, and challenges, which are presented in this book will have their impact and contribution in the design and development of modern and effective healthcare systems.

Secure multimodal biometric authentication is a process of using multiple biometric traits to authenticate a user's identity. This approach offers increased security by combining the strengths of different biometric authentication techniques, such as fingerprint recognition, iris recognition, face recognition, voice recognition, and behavioral biometrics. By combining multiple biometric traits, the risk of false positives and false negatives can be reduced, providing a more reliable and secure authentication process.Machine learning and artificial intelligence algorithms can be used to develop secure multimodal biometric authentication systems that can adapt to changing user behavior and environmental conditions. Deep learning techniques can also be used to enhance the accuracy and efficiency of biometric recognition.Cryptography plays a vital role in securing the biometric data and ensuring the privacy of the users. The biometric data should be encrypted before transmission, and the encryption keys must be securely stored and managed.Overall, secure multimodal biometric authentication can provide a reliable and secure authentication process for user identification and access control. The combination of different biometric traits and machine learning algorithms can enhance the accuracy and efficiency of the authentication process, ensuring the privacy and security of the users

Walking is a fundamental and common method of transport in all social orders the world over. Almost every trip starts and windup with walking. The routine walk may reduce or cure cardiovascular and obesity-related illnesses which are also beneficial for good human health. Unfortunately, in certain circumstances walking can bring out amplify the risk of road traffic crashes and/or injury [1]. Developing nations in Asia are right now confronted with issues, for example, expanding urbanization and requirements for more safety and luxurious travel to enjoy a standard life pattern. Indian cities are flattering more spirited worldwide especially in three key areas: Aerospace, Defence, Transport and Support Service. Vehicles mobility, without any doubt, is the key element of transport systems. A good transport and support service primarily depends on safety and a specified time frame.

This book constitutes the refereed proceedings of the 18th International Conference on Frontiers in Handwriting Recognition, ICFHR 2022, which took place in Hyderabad, India, during December 4-7, 2022.The 36 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 61 submissions. The contributions were organized in topical sections as follows: Historical Document Processing; Signature Verification and Writer Identification; Symbol and Graphics Recognition; Handwriting Recognition and Understanding; Handwriting Datasets and Synthetic Handwriting Generation; Document Analysis and Processing.

This volume constitutes the papers of two workshops which were held in conjunctionwith the First International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2020, Virtual Event, in November 4-6, 2020 and Second International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2021, Virtual Event, in October 25-27, 2021.The 11 revised full papers presented in this book were carefully reviewed and selectedfrom 53 submissions.