الصفحة 4
الصفحة 4
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 biomedical application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
Classification of covid-19 in lung images
The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of China in December 2019, spread rapidly around the world and became a pandemic. It has caused a devastating effect on both daily lives, public health, and the global economy. It is critical to detect the positive cases as early as possible so as to prevent the further spread of this epidemic and to quickly treat affected patients. The need for auxiliary diagnostic tools has increased as there are no accurate automated toolkits available. Recent findings obtained using radiology imaging techniques suggest that such images contain salient information about the COVID-19 virus. Application of advanced artificial intelligence (AI) techniques coupled with radiological imaging can be helpful for the accurate detection of this disease, and can also be assistive to overcome the problem of a lack of specialized physicians in remote villages.
Cartoony story app = تطبيق قصة كارتونية
The translation of textual narratives into immersive visual representations poses a significant challenge in the field of artificial intelligence. Traditional cartoon generation techniques face formidable technical challenges and require substantial resources. Research efforts towards direct video synthesis from text have encountered obstacles in developing efficient techniques. In parallel, researchers propose an alternative approach involving the generation of dynamic sequences of images portraying children's story narratives. This approach includes applying various visual effects to highlight motion, interaction, and excitement in storytelling. By dynamically generating a sequence of images reflecting the narrative's progression and applying diverse visual effects, this alternative method offers a flexible and practical solution to cartoon generation challenges, providing an efficient and effective experience akin to video while retaining the magical appeal of visual storytelling. ...
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ; 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I
The content of thebook covers the current state-of-the-art literature on federated learning applications for cancer research and Vclinical oncology analysis, as well as an overview of the deep learning approaches improving the current standard of care for brain lesions and current neuroimaging challenges. It is also focusing on the accepted BrainLes workshop submissions, is to provide an overview of new advances of medical image analysis in all the aforementioned brain pathologies. It brings together researchers from the medical image analysis domain, neurologists, and radiologists working on at least one of these diseases. The aim is to consider neuroimaging biomarkers used for one disease applied to the other diseases.
Biomedical data mining for information retrieval : Methodologies, techniques, and applications
Discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally.
Big Data in Bioeconomy : Results from the European DataBio Project
This book presents the comprehensive outcome of The European DataBio Project, which examined new data-driven methods to shape a bioeconomy. These methods are used to develop new and sustainable ways to use forest, farm and fishery resources.
Beginning Ubuntu Linux : From novice to professional
Beginning Ubuntu Linux is the perfect guide for those switching to the world's favorite Linux. The new edition has been thoroughly updated to cover technology introduced in the 6.10 release. You'll learn how to install Linux, set up your hardware and software, customize the desktop experience, browse the Web and send/receive e-mail, play back audio and video, edit digital images, use the OpenOffice.org office suite, and more.
Beginning GIMP : From novice to professional
Beginning GIMP: From Novice to Professional explains how to use the open source image manipulation program, GIMP version 2.4. You'll learn how to install GIMP on Windows, Linux, and MacOS X platforms. Once you've installed the application, you'll learn about the interface and configuration options, and then jump into a quick–and–simple project to familiarize yourself even further. With four–color graphics and screenshots throughout, you'll learn how to prepare camera images for display on web pagesincluding functions like rescaling, cropping, and balancing color. The book also explains with great detail how to utilize layers, paths, and masks. You'll also learn how to draw lines and shapes, use patterns and gradients, and even create your own brushes, patterns, and gradients.
Artificial intelligence techniques for satellite image analysis
The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind. Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. It can be also used as a supplementary textbook for graduate students in various engineering branches related to image processing.
Artificial intelligence for multisource geospatial information
Collects 10 original research contributions published in the Special Issue entitled “Artificial Intelligence for Multisource Geospatial Information” of the ISPRS International Journal of Geo-Information. The focus is on different methods of Geospatial Artificial Intelligence (GeoAI) based on deep learning using different network architectures, clustering, soft computing, and semantic approaches. They are proposed to deal with a variety of Geospatial Big Data (GBD), such as georeferenced texts and photos in social networks, remote sensing images, cartographic maps, multidimensional geo databases, metadata in spatial data infrastructures, and for different tasks, such as for multisource georeferenced text integration and geodata flexible querying, for social sensing by applying sentiment analysis, clustering and geo analysis, for segmentation of roads, clouds and snow, and for detection of small targets and people on the streets.
Artificial Intelligence Applications for Health Care
Covers topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided.
Articulated Motion and Doformable Objects ; 4th International Conference, AMDO 2006, Port d'Andratx, Mallorca, Spain, July 11-14, 2006, Proceedings
The subject of the conference was ongoing research in articulated motionon a sequence of images and sophisticated models for deformable objects. Thegoals of these areas are to understand and interpret the motion of complexobjects that can be found in sequences of images in the real world. The maintopics considered as priority were: geometric and physical deformable models,motion analysis, articulated models and animation, modelling and visualizationof deformable models, deformable models applications, motion analysis applica-tions, single or multiple human motion analysis and synthesis, face modelling,tracking, recovering and recognition models, virtual and augmentedreality, haptics devices, biometrics techniques.
Alternative breast imaging : Four model-based approaches
Medical imaging has been transformed over the past 30 years by the advent of computerized tomography (CT), magnetic resonance imaging (MRI), and various advances in x-ray and ultrasonic techniques. An enabling force behind this progress has been the (so far) exponentially increasing power of computers, which has made it practical to explore fundamentally new approaches. In particular, what our group terms "model-based" modalities-which produce tissue property images from data using nonlinear, iterative numerical modeling techniques-have become increasingly feasible. Alternative Breast Imaging: Four Model-Based Approaches explores our research on four such modalities, particularly with regard to imaging of the breast: (1) MR elastography (MRE), (2) electrical impedance spectroscopy (EIS), (3) microwave imaging spectroscopy (MIS), and (4) near infrared spectroscopic imaging (NIS).
Advances in Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry ; International Conference, MDA 2006/2007, Leipzig, Germany, July 18, 2007, Selected Papers
The automatic analysis of images and signals in medicine, biotechnology, and chemistry is a challenging and demanding field. Signal-producing procedures by microscopes, spectrometers, and other sensors have found their way into wide fields of medicine, biotechnology, economy, and environmental analysis. With this arises the problem of the automatic mass analysis of signal information. Signal-interpreting systems which generate automatically the desired target statements from the signals are therefore of compelling necessity. The continuation of mass analyses on the basis of classical procedures leads to investments of proportions that are not feasible. New procedures and system architectures are therefore required. The goals of this: Provide a forum for identifying important contributions and opportunities for research on mass data analysis on microscopic images Promote the systematic study of how to apply automatic image analysis and interpretation procedures to that field Show case applications of mass data analysis in biology, medicine, and chemistry Topics of interest include (but are not limited to): Techniques and developments of signal and image producing procedures Object matching and object tracking in microscopic and video microscopic images 1D, 2D, and 3D shape analysis and description
Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry ; 3rd International Conference, MDA 2008 Leipzig, Germany, July 14, 2008 Proceedings
Presents the broad and growing scientific evidence linking mass data analysis with challenging problems in medicine, biotechnology and chemistry.
Advances in image enhancement
In the era of the internet of things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development of camera hardware quality, i.e., the resolution and exposure time of cameras, which may require high computational costs. As an alternative, image enhancement techniques can exact salient features to improve the quality of captured images according to the differences in diverse features, although they suffer from some challenges, i.e., a low contrast, artifacts, and overexposure, thus making it decidedly necessary to determine how to use advanced image enhancement techniques.
Advances in Image and Video Technology ; 1st Pacific Rim Symposium, PSIVT 2006, Hsinchu, Taiwan, December 10-13, 2006, Proceedings
The conference of the 1st IEEE Pacisc-Rim Symposium on Image and Video Technology (PSIVT 2006) was held at Hsinchu, Taiwan, Republic of China, on December 11–13, 2006. This volume contains papers selected for presentation at this conference. The aim of this conference was to bring together theoretical advances and practical implementations contributing to, or being involved in, image and video technology. PSIVT 2006 featured a comprehensive program including tutorials, keynote and invited talks, oral paper presentations, and posters. We received 450 s- missions from 22 countries and accepted 141 papers among those (i.e., de?ning an acceptance rate of 31.3%). The intention was to establish PSIVT as a t- quality series of symposia. Decisions were discult sometimes, but we hope that the ?nal result is acceptable to all involved.
Advances in Data Mining ; Vol. 4065 : Applications in Medicine, Web Mining, Marketing, Image and Signal Mining, 6th Industrial Conference on Data Mining, ICDM 2006, Leipzig, Germany, July 14-15, 2006, Proceedings
The Industrial Conference on Data Mining ICDM-Leipzig was the sixth event in a series of annual events which started in 2000. We are pleased to note that the topic data mining with special emphasis on real-world applications has been adopted by so many researchers all over the world into their research work. We received 156 papers from 19 different countries. The main topics are data mining in medicine and marketing, web mining, mining of images and signals, theoretical aspects of data mining, and aspects of data mining that bundle a series of different data mining applications such as intrusion detection, knowledge management, manufacturing process control, time-series mining and criminal investigations. The Program Committee worked hard in order to select the best papers.
Advances in conceptual modeling : Challenges and opportunities ; ER 2008 Workshops CMLSA, ECDM, FP-UML, M2AS, RIGiM, SeCoGIS, WISM, Barcelona Spain, October 20-23, 2008. Proceedings
Constitutes the refereed joint proceedings of seven international workshops held in conjunction with the 27th International Conference on Conceptual Modeling, ER 2008, in Barcelona, Spain, in October 2008.
