الصفحة 101
الصفحة 101
Machine Learning in Document Analysis and Recognition
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi?ers.
Machine Learning in Dentistry
This book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties.
Machine Learning for Multimodal Interaction ; Vol.3361 : 1st International Workshop, MLMI 2004, Martigny, Switzerland, June 21-23, 2004, Revised Selected Papers
his book contains a selection of refereed papers presented at the 1st Wo- shop on Machine Learning for Multimodal Interaction (MLMI 2004), held at the “Centre du Parc,” Martigny, Switzerland, during June 21–23, 2004. The workshop was organized and sponsored jointly by three European projects, – AMI, Augmented Multiparty Interaction, http://www.amiproject.org – PASCAL, Pattern Analysis, Statistical Modeling and Computational Learning, http://www.pascal-network.org – M4, Multi-modal Meeting Manager, http://www.m4project.org as well as the Swiss National Centre of Competence in Research (NCCR): – IM2: Interactive Multimodal Information Management, http://www.im2.ch MLMI 2004 was thus sponsored by the European Commission and the Swiss National Science Foundation.
Machine Learning for Multimodal Interaction ; 4th International Workshop, MLMI 2007, Brno, Czech Republic, June 28-30, 2007, Revised Selected Papers
This book contains a selection of revised papers from the 4th Workshop on Machine Learning for Multimodal Interaction (MLMI 2007), which took place in Brno, Czech Republic, during June 28 30, 2007. As in the previous editions of the MLMI series, the 26 chapters of this book cover a large area of topics, from multimodal processing and human computer interaction to video, audio, speech and language processing. The application of machine learning techniques to problems arising in these felds and the design and analysis of software
Machine Learning for Multimedia Content Analysis
Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image collectively conveys certain visual content to viewers. A TV video program consists of both audio and image streams that unfold the underlying story. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly.
Machine learning for cyber-physical systems: selected papers from the international conference ML4CPS 2023
Contains selected papers from the international conference ML4CPS – Machine Learning for Cyber-Physical Systems, which was held in Hamburg (Germany), from 29 to 31 March 2023. Cyber-physical systems are adaptive and learning: they analyze their environment and, based on observations, learn patterns, associations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnostics. Machine learning is the key technology for these developments.
Machine Learning for Cyber Security ; 3rd International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part II
Constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Agents : Attack and Defence
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.
Machine Learning for Audio, Image and Video Analysis : Theory and Applications
The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing, while the third part focuses on applications and shows how techniques are applied in actual problems. The fourth part contains detailed appendices that provide notions about the main mathematical instruments used throughout the text
Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II
Constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008.The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer.
Machine Learning and Data Mining in Pattern Recognition ; 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Machine Learning : Modeling Data Locally and Globally
Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either "local learning"or "global learning."This theory not only connects previous machine learning methods, or serves as roadmap in various models, but – more importantly – it also motivates a theory that can learn from data both locally and globally. This would help the researchers gain a deeper insight and comprehensive understanding of the techniques in this field. The book reviews current topics,new theories and applications.
Machine Intelligence and Big Data Analytics for Cybersecurity Applications
Presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field.
Macchine matematiche : Dalla storia alla scuola = Mathematical Machines: From History to School
Presents the main mathematical machines for drawing curves, for applying geometrical transformations or for making classical perspectives.The publication constitutes an example of how history of mathematics may be useful for teaching today’s mathematics.
Low Thermal Expansion Glass Ceramics
Describes the fundamental principles, the manufacturing process, and applications of low thermal expansion glass ceramics. The composition, structure, and stability of polycrystalline materials having a low thermal expansion are described, and it is shown how low thermal expansion glass ceramics can be manufactured from appropriately chosen glass compositions. Examples illustrate the formation of this type of glass ceramic by utilizing normal production processes together with controlled crystallization. Thus glass ceramics with thermal coefficients of expansion of less than 0.3 x 10(-6)K(-1) can be obtained. Even for the mass production of high-quality cooktop panels (Ceran®., oven windows, and other household appliances a high reproducibility of the properties is achieved. Special glass ceramics (Zerodur®. for technological and scientific applications such as high-precision optics or large astronomical mirrors are likewise discussed. The completely revised edition also features new sections on glass-ceramic applications, with details on their performance, CDC-grinding, and laser gyroscopes containing Zerodur®..
Low Molecular Mass Gelators : Design, Self-Assembly, Function
Chapter 1 presents the physical principles of the growth mechanism of fiber and fiber network with LMGs, as treated on the basis of the heterogeneous nucleation model. in Chaps. 2 and 3, respectively. These chapters are intended to outline useful synthetic guidelines for the generation of an ever-increasing variety of molecular architectures within these two families of gelators. Recent developments in the chemistry of nucleobase-containing LMGs are described in Chap. 4. Hydrogen-bonding within these molecular systems involves complementary base pair formation, a process relevant to DNA double-helix formation The self-assembly of chiral organo- or hydrogelators is the subject of Chap. 5. result from the orthogonal self-assembly of liquid crystals and LMGs are presented in Chap. 6. The volume concludes with Chap. 7, a review of the emerging field of dendritic gels.
Low impact building : Housing using renewable materials
Guides to the designs, technologies and materials that really make green buildings work will help architects, specifiers and clients make informed choices, based on reliable technical information. Low Impact Building: Housing using Renewable Materials is about changing the way we build houses to reduce their 'carbon' footprint and to minimise environmental damage. One of the ways this can be done is by reducing the energy and environmental impact of the materials and resources used to construct buildings by choosing alternative products and systems. In particular, we need to recognise the potential for using natural and renewable construction materials as a way to reduce both carbon emissions but also build in a more benign and healthy way.
Lotus japonicus Handbook
Represents the first effort to compile basic descriptions and methods for research in Lotus, including symbiotic processes, cell and molecular biology protocols, functional genomics, mutants, gene tagging and genetic analysis, transformation and reverse genetic analysis, primary and secondary metabolism, and an exhaustive update of the scientific literature available on this plant.
Long-Term Preservation of Digital Documents : Principles and Practices
Key to our culture is that we can disseminate information, and then maintain and access it over time. While we are rapidly advancing from vulnerable physical solutions to superior, digital media, preserving and using data over the long term involves complicated research challenges and organization efforts. Uwe Borghoff and his coauthors address the problem of storing, reading, and using digital data for periods longer than 50 years. They briefly describe several markup and document description languages like TIFF, PDF, HTML, and XML, explain the most important techniques such as migration and emulation, and present the OAIS (Open Archival Information System) Reference Model. To complement this background information on the technology issues the authors present the most relevant international preservation projects, such as the Dublin Core Metadata Initiative, and experiences from sample projects run by the Cornell University Library and the National Library of the Netherlands. A rated survey list of available systems and tools completes the book.
