Download or read book Point Cloud Processing for Environmental Analysis in Autonomous Driving using Deep Learning written by Martin Simon and published by BoD – Books on Demand. This book was released on 2023-01-01 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous self-driving cars need a very precise perception system of their environment, working for every conceivable scenario. Therefore, different kinds of sensor types, such as lidar scanners, are in use. This thesis contributes highly efficient algorithms for 3D object recognition to the scientific community. It provides a Deep Neural Network with specific layers and a novel loss to safely localize and estimate the orientation of objects from point clouds originating from lidar sensors. First, a single-shot 3D object detector is developed that outputs dense predictions in only one forward pass. Next, this detector is refined by fusing complementary semantic features from cameras and joint probabilistic tracking to stabilize predictions and filter outliers. The last part presents an evaluation of data from automotive-grade lidar scanners. A Generative Adversarial Network is also being developed as an alternative for target-specific artificial data generation.
Download or read book Neural Computing for Advanced Applications written by Haijun Zhang and published by Springer Nature. This book was released on 2022-10-20 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume Proceedings set CCIS 1637 and 1638 constitutes the refereed proceedings of the Third International Conference on Neural Computing for Advanced Applications, NCAA 2022, held in Jinan, China, during July 8–10, 2022. The 77 papers included in these proceedings were carefully reviewed and selected from 205 submissions. These papers were categorized into 10 technical tracks, i.e., neural network theory, and cognitive sciences, machine learning, data mining, data security & privacy protection, and data-driven applications, computational intelligence, nature-inspired optimizers, and their engineering applications, cloud/edge/fog computing, the Internet of Things/Vehicles (IoT/IoV), and their system optimization, control systems, network synchronization, system integration, and industrial artificial intelligence, fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences, computer vision, image processing, and their industrial applications, natural language processing, machine translation, knowledge graphs, and their applications, Neural computing-based fault diagnosis, fault forecasting, prognostic management, and system modeling, and Spreading dynamics, forecasting, and other intelligent techniques against coronavirus disease (COVID-19).
Download or read book Deep Learning for Autonomous and Driver Assistant Systems written by Farzan Nowruzi and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The main goal of autonomous driving is the complete removal of human supervision from the work-flow of autonomous vehicles. This objective represents an opportunity for enhancing quality of life by reducing traffic, removing parking spaces in cities, increasing collective fuel efficiency, and reducing accidents. As autonomous driving is progressively getting integrated into our daily lives, viable solutions are required for its challenges. Artificial intelligence is the main technology that provides intelligent agents with the capability to perceive visual information in a way similar or even superior to human agents. In recent years the deep learning methods showed their outstanding power in dealing with various data processing tasks. Most of the open problems in autonomous driving are focused on the surrounding environment, and some are within the cabin. This dissertation presents solutions to selected problems in both domains using deep learning methods with various sensor modalities. We introduce a model that is able to extract the geometric relationship between two camera images. These results then allow us to proceed with the development of a model to solve geometric transformation in a sequence of point-cloud observations to address the odometry problem. Our proposed method is directly consuming the point-clouds in real-time. Further, we develop the first publicly available comprehensive Radar dataset and propose an open space segmentation model for this task. Lastly, we present a method that uses thermal imaging within the vehicle to count the number of passengers. The thermal images are hiding most of the visual features of passengers and better respect their privacy.
Download or read book Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment written by Zhijun Chen and published by Elsevier. This book was released on 2024-04-19 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of constructing advanced Autonomous Driving Maps. It includes coverage of such methods as: fusion target perception (based on vehicle vision and millimeter wave radar), cross-field of view object perception, vehicle motion recognition (based on vehicle road fusion information), vehicle trajectory prediction (based on improved hybrid neural network) and the driving map construction method driven by road perception fusion. An Autonomous Driving Map is used for optimization of not only for a single vehicle, but also for the entire traffic system.
Download or read book Autonomous driving algorithms and Its IC Design written by Jianfeng Ren and published by Springer Nature. This book was released on 2023-08-09 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid development of artificial intelligence and the emergence of various new sensors, autonomous driving has grown in popularity in recent years. The implementation of autonomous driving requires new sources of sensory data, such as cameras, radars, and lidars, and the algorithm processing requires a high degree of parallel computing. In this regard, traditional CPUs have insufficient computing power, while DSPs are good at image processing but lack sufficient performance for deep learning. Although GPUs are good at training, they are too “power-hungry,” which can affect vehicle performance. Therefore, this book looks to the future, arguing that custom ASICs are bound to become mainstream. With the goal of ICs design for autonomous driving, this book discusses the theory and engineering practice of designing future-oriented autonomous driving SoC chips. The content is divided into thirteen chapters, the first chapter mainly introduces readers to the current challenges and research directions in autonomous driving. Chapters 2–6 focus on algorithm design for perception and planning control. Chapters 7–10 address the optimization of deep learning models and the design of deep learning chips, while Chapters 11-12 cover automatic driving software architecture design. Chapter 13 discusses the 5G application on autonomous drving. This book is suitable for all undergraduates, graduate students, and engineering technicians who are interested in autonomous driving.
Download or read book Deep Learning for Autonomous Vehicle Control written by Sampo Kuutti and published by Morgan & Claypool Publishers. This book was released on 2019-08-08 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of autonomous vehicles, one aspect of which is robust and adaptable vehicle control. Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalizing previously learned rules to new scenarios. For these reasons, the use of deep neural networks for vehicle control has gained significant interest. In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field.
Download or read book ROBOT2022 Fifth Iberian Robotics Conference written by Danilo Tardioli and published by Springer Nature. This book was released on 2022-11-18 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a selection of papers accepted for presentation and discussion at ROBOT 2022—Fifth Iberian Robotics Conference, held in Zaragoza, Spain, on November 23-25, 2022. ROBOT 2022 is part of a series of conferences that are a joint organization of SEIDROB—Sociedad Española para la Investigación y Desarrollo en Robótica/Spanish Society for Research and Development in Robotics, and SPR—Sociedade Portuguesa de Robótica/Portuguese Society for Robotic. ROBOT 2022 builds upon several previous successful events, including three biennial workshops and the four previous editions of the Iberian Robotics Conference, and is focused on presenting the research and development of new applications, on the field of Robotics, in the Iberian Peninsula, although open to research and delegates from other countries. ROBOT 2022 featured four plenary talks on state-of-the-art subjects on robotics and 15 special sessions, plus a main/general robotics track. In total, after a careful review process, 98 high-quality papers were selected for publication, with a total of 219 unique authors, from 22 countries.
Download or read book Point Cloud Compression written by Ge Li and published by Springer Nature. This book was released on with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Signal Processing and Analysis of Electrical Circuit written by Adam Glowacz and published by MDPI. This book was released on 2020-03-13 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Special Issue with 35 published articles shows the significance of the topic “Signal Processing and Analysis of Electrical Circuit”. This topic has been gaining increasing attention in recent times. The presented articles can be categorized into four different areas: signal processing and analysis methods of electrical circuits; electrical measurement technology; applications of signal processing of electrical equipment; fault diagnosis of electrical circuits. It is a fact that the development of electrical systems, signal processing methods, and circuits has been accelerating. Electronics applications related to electrical circuits and signal processing methods have gained noticeable attention in recent times. The methods of signal processing and electrical circuits are widely used by engineers and scientists all over the world. The constituent papers represent a significant contribution to electronics and present applications that can be used in industry. Further improvements to the presented approaches are required for realizing their full potential.
Download or read book Autonomous Driving Perception written by Rui Fan and published by Springer Nature. This book was released on 2023-10-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the captivating world of computer vision and deep learning for autonomous driving with our comprehensive and in-depth guide. Immerse yourself in an in-depth exploration of cutting-edge topics, carefully crafted to engage tertiary students and ignite the curiosity of researchers and professionals in the field. From fundamental principles to practical applications, this comprehensive guide offers a gentle introduction, expert evaluations of state-of-the-art methods, and inspiring research directions. With a broad range of topics covered, it is also an invaluable resource for university programs offering computer vision and deep learning courses. This book provides clear and simplified algorithm descriptions, making it easy for beginners to understand the complex concepts. We also include carefully selected problems and examples to help reinforce your learning. Don't miss out on this essential guide to computer vision and deep learning for autonomous driving.
Download or read book Learning to Drive written by David Michael Stavens and published by Stanford University. This book was released on 2011 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every year, 1.2 million people die in automobile accidents and up to 50 million are injured. Many of these deaths are due to driver error and other preventable causes. Autonomous or highly aware cars have the potential to positively impact tens of millions of people. Building an autonomous car is not easy. Although the absolute number of traffic fatalities is tragically large, the failure rate of human driving is actually very small. A human driver makes a fatal mistake once in about 88 million miles. As a co-founding member of the Stanford Racing Team, we have built several relevant prototypes of autonomous cars. These include Stanley, the winner of the 2005 DARPA Grand Challenge and Junior, the car that took second place in the 2007 Urban Challenge. These prototypes demonstrate that autonomous vehicles can be successful in challenging environments. Nevertheless, reliable, cost-effective perception under uncertainty is a major challenge to the deployment of robotic cars in practice. This dissertation presents selected perception technologies for autonomous driving in the context of Stanford's autonomous cars. We consider speed selection in response to terrain conditions, smooth road finding, improved visual feature optimization, and cost effective car detection. Our work does not rely on manual engineering or even supervised machine learning. Rather, the car learns on its own, training itself without human teaching or labeling. We show this "self-supervised" learning often meets or exceeds traditional methods. Furthermore, we feel self-supervised learning is the only approach with the potential to provide the very low failure rates necessary to improve on human driving performance.
Download or read book ECAI 2023 written by K. Gal and published by IOS Press. This book was released on 2023-10-18 with total page 3328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
Download or read book Image Analysis and Processing ICIAP 2022 written by Stan Sclaroff and published by Springer Nature. This book was released on 2022-05-16 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 13231, 13232, and 13233 constitutes the refereed proceedings of the 21st International Conference on Image Analysis and Processing, ICIAP 2022, which was held during May 23-27, 2022, in Lecce, Italy, The 168 papers included in the proceedings were carefully reviewed and selected from 307 submissions. They deal with video analysis and understanding; pattern recognition and machine learning; deep learning; multi-view geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; digital forensics and biometrics; image processing for cultural heritage; robot vision; etc.
Download or read book Robust Environmental Perception and Reliability Control for Intelligent Vehicles written by Huihui Pan and published by Springer Nature. This book was released on 2023-11-25 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes. Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy. Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods. Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers. Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account. Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.
Download or read book Frontiers of Digital Transformation written by Kazuya Takeda and published by Springer Nature. This book was released on 2021-05-18 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proposing the concept of real-world data circulation (RWDC), this book presents various practical and industry-related studies in human, mechanical, and social data domains. RWDC is a new field of study, established by the information technology (IT) community. In the real world, the speed of data transmission between computers surpassed that of human communications long ago and has since expanded exponentially. As a result, the origin of the majority of data has become non-human, mechanical, or natural sources; in fact, humans are merely the source of a small part of the current data explosion. Such expanding data transmission does not simply consist of single source–destination pairs, but actually circulates over a complex network connecting numerous sources and destinations. Such circulation is an important aspect of the underlying systems. Based on this concept, in order to tame and control the massive amount of data originating from non-human sources, the authors have been considering the insertion of acquisition, analysis, and implementation processes in the flow of data circulation. This book introduces the outcome of the RWDC degree program organized at Nagoya University, Japan, collecting contributions from graduate students enrolled in the program from various research fields targeting diverse applications. Through examples of RWDC, the resulting creation of social value is illustrated. This book will be useful not only for those working on the topics discussed, but also to anyone who is interested in RWDC, digital transformation, and Industry 4.0.
Download or read book Mastering Robotics Research written by Rob Botwright and published by Rob Botwright. This book was released on 101-01-01 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 🚀 Unlock Your Potential in Robotics Research with Our Book Bundle! 🤖 Are you passionate about robotics? Do you dream of becoming an expert in this exciting field? Look no further! Introducing the "Mastering Robotics Research" book bundle—a comprehensive collection of knowledge that will take you from an enthusiastic beginner to a seasoned expert. 📚 Book 1: Introduction to Robotics Research: A Beginner's Guide · Dive into the captivating history of robotics. · Master essential terminologies and concepts. · Lay a solid foundation for your journey into robotics research. 📚 Book 2: Fundamentals of Robotics Research: Building a Strong Foundation · Explore the mechanics of robotics, including kinematics and dynamics. · Understand sensors, actuators, and more. · Equip yourself with the fundamental knowledge required to excel in robotics research. 📚 Book 3: Advanced Techniques in Robotics Research: Becoming a Specialist · Delve into cutting-edge technologies like computer vision and machine learning. · Develop advanced control systems expertise. · Specialize in niche areas and elevate your research skills. 📚 Book 4: Mastering Robotics Research: From Enthusiast to Expert · Ascend to the pinnacle of robotics expertise. · Tackle real-world challenges and innovate. · Discover how to contribute groundbreaking research to the field. 🌟 Why Choose Our Book Bundle? · 🧠 Comprehensive Learning: Cover the entire spectrum of robotics research, from basics to specialization. · 🤖 Hands-On Experience: Practical examples and projects ensure you learn by doing. · 📈 Career Advancement: Boost your career prospects by becoming a robotics expert. · 📖 Expert Guidance: Learn from experienced authors and researchers in the field. 🎁 BONUS: Order now, and receive additional resources to complement your learning journey! Whether you're an aspiring researcher, a robotics enthusiast, or a professional looking to deepen your knowledge, our book bundle has something for you. Don't miss this opportunity to master robotics research and become the expert you've always wanted to be! 🔥 Limited Time Offer: Grab your "Mastering Robotics Research" book bundle now and embark on a transformative journey in the world of robotics. Your expertise awaits! Order your bundle today and unlock a world of robotics knowledge!
Download or read book RGB D Image Analysis and Processing written by Paul L. Rosin and published by Springer Nature. This book was released on 2019-10-26 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.
