الصفحة 8
الصفحة 8
Fundamentals of image data mining : Analysis, features, classification and retrieval
Presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments. Topics and features: Describes essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms / Develops many new exercises (most with MATLAB code and instructions) / Includes review summaries at the end of each chapter / Analyses state-of-the-art models, algorithms, and procedures for image mining / Integrates new sections on pre-processing, discrete cosine transform, and statistical inference and testing / Demonstrates how features like color, texture, and shape can be mined or extracted for image representation / Applies powerful classification approaches: Bayesian classification, support vector machines, neural / networks, and decision trees / Implements imaging techniques for indexing, ranking, and presentation, as well as database visualization
Fundamentals and Methods of Machine and Deep Learning : Algorithms, Tools, and Applications
provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. In recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field.
Functional Imaging and Modeling of the Heart ; 4th International Conference, Salt Lake City, UT, USA, June 7-9, 2007
This book constitutes the refereed proceedings of the 4th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2007, held in Salt Lake City, UT, USA in June 2007.
Functional imaging and modeling of the heart ; 3rd International workshop, FIMH 2005, Barcelona, Spain, June 2-4, 2005, Proceedings
The FIMH conference was the ?rst attempt to agglutinate researchers from several complementary but often i- lated ?elds: cardiac imaging, signal and image processing, applied mathematics and physics, biomedical engineering and computer science, cardiology, radi- ogy, biology, and physiology. In the ?rst two editions, the conference received an enthusiastic acceptance by experts of all these communities. FIMH was ori- nally started as a European event and has increasingly attracted more and more people from the US and Asia. This edition of FIMH received the largest number of submissions so far with a result of 47 papers being accepted as either oral presentations or posters. There were a number of submissions from non-EU institutions which con?rms the growing interest in this series of meetings. All papers were reviewed by up to four reviewers. The accepted contributions were organized into 8 oral sessions and 3 poster sessions complemented by a number of invited talks. This year we tried to allocate as many papers as possible as oral presentations to facilitate more active participation and to stimulate multidisciplinary discussions.
Frontiers in Algorithmics ; 2nd Annual International Workshop, FAW 2008, Changsha, China, June 19-21, 2008, Proceeedings
This book constitutes the refereed proceedings of the Second International Frontiers of Algorithmics Workshop, FAW 2008, held in Changsha, China, in June 2008.The 33 revised full papers presented together with the abstracts of 3 invited talks were carefully reviewed and selected from 80 submissions. The papers were selected for 9 special focus tracks in the areas of biomedical informatics, discrete structures, geometric information processing and communication, games and incentive analysis.
Fractals in Engineering : New Trends in Theory and Applications
The strong potential of this research can be seen in real industrial situations with recent progress being made in areas such as chemical engineering, internet traffic, physics and finance. Image processing continues to be a major field of application for fractal analysis and is well-represented here. Consisting of papers written by a world-wide pool of experts, the multidisciplinary approach of this third volume will be of particular interest to industrial researchers and practitioners as well as to academics from many backgrounds.
Foundation PHP for Dreamweaver 8
In this book, we look specifically at using Dreamweaver's built-in server behaviors to build dynamic web sites using PHP and MySQL, the world's most popular open source server-side language and database server combination, which are both reliable, powerful, and open source (and therefore free to use). This version of Dreamweaver includes more powerful support for PHP and MySQL than ever before, and we'll show you how to make this work for you. No previous experience of PHP or MySQL is necessary to use this book. Examples built throughout the book include a content management system, and an online image gallery. All examples are designed to meet modern usability requirements and be web standards-compliant.
Foundation models for natural language processing : pre-trained language models integrating media
Covers basic natural language processing models, pre-trained language models BERT, GPT, and sequence-to-sequence converters, as well as the concepts of self-attention and context-sensitive embedding. Various approaches to improving these models are then discussed, such as expanding the pre-training parameters, increasing the length of input texts, or incorporating additional knowledge. An overview of the best performing models is then provided for about twenty application areas, e.g., question answering, translation, story generation, dialogue systems, image generation from text, etc. For each application area, the strengths and weaknesses of existing models are discussed, and an overview of further developments is provided. In addition, links to freely available code are provided. The concluding chapter summarizes the economic opportunities, risk mitigation, and potential developments of AI.
Food lens = فود لينس
Food lens is an innovative application designed to revolutionize dietary management by leveraging advanced image recognition and nutritional analysis. The primary objective of this senior project is to develop a user-friendly tool that identifies various foods through a camera interface and provides detailed nutritional information. This application not only enhances the user's understanding of their dietary intake but also assists in achieving personalized health and fitness goals. The core functionality of Food Lens involves the integration of a robust image recognition system capable of accurately identifying a wide range of foods. Upon identification, the application retrieves comprehensive nutritional data, including calorie content, macronutrient distribution (proteins, fats, carbohydrates), and essential micronutrients (vitamins and minerals). This data is then seamlessly integrated into the user's dietary profile. Food Lens is designed to track the user's daily caloric intake and compare it against personalized recommendations based on age, gender, weight, height, and activity level. By maintaining a dynamic record of consumed foods, the application provides real-time feedback on the user’s nutritional progress. This feature is particularly beneficial for individuals aiming to manage weight, address dietary restrictions, or improve overall health.
Fashionity
This project is an AI fashion design system to generate fashion images based on user textual description. The proposed system incorporates advanced technology for dissemination and machine translation with the aim of facilitating a seamless user experience for input in both Arabic and English languages. Moreover, the project encompasses the incorporation of a recommendation system that proposes appropriate visual content based on user style. The primary objective of this project is to develop a robust framework capable of generating high-quality images based on textual descriptions, providing recommendations for similar clothing items, and facilitating the retrieval of photographic and apparel articles through image search.
Fashion forge
"Fashion forge" revolutionizes clothing shopping with a cutting-edge mobile application. This AI-powered platform empowers users to describe their dream garment and visualize it instantly, bridging the gap between imagination and reality for fashion-forward users and designers. A recommendation system tailors clothing suggestions based on user preferences, while stores leverage a dedicated social platform for effective marketing. "Fashion Forge" fosters a connected fashion community, empowering users, designers, and stores alike.
Face Biometrics for Personal Identification : Multi-Sensory Multi-Modal Systems
This book provides an ample coverage of theoretical and experimental state-of-the-art work as well as new trends and directions in the biometrics field. It offers students and software engineers a thorough understanding of how some core low-level building blocks of a multi-biometric system are implemented. While this book covers a range of biometric traits including facial geometry, 3D ear form, fingerprints, vein structure, voice, and gait, its main emphasis is placed on multi-sensory and multi-modal face biometrics algorithms and systems. "Multi-sensory" refers to combining data from two or more biometric sensors, such as synchronized reflectance-based and temperature-based face images. "Multi-modal" biometrics means fusing two or more biometric modalities, like face images and voice timber. The first part addresses new and emerging face biometrics. Emphasis is placed on biometric systems where single sensor and single modality are employed in challenging imaging conditions. The second part on multi-sensory face biometrics deals with the personal identification task in challenging variable illuminations and outdoor operating scenarios by employing visible and thermal sensors. The third part of the book focuses on multi-modal face biometrics by integrating voice, ear, and gait modalities with facial data. The last part presents generic chapters on multi-biometrics fusion methodologies and performance prediction techniques.
Explainable AI with Python
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others.
Evolving Connectionist Systems : The Knowledge Engineering Approach
Evolving Connectionist Systems is aimed at all those interested in developing and using intelligent computational models and systems to solve challenging real world problems in computer science, engineering, bioinformatics and neuroinformatics. The book challenges scientists and practitioners with open questions about future creation of new information models inspired by Nature. This edition includes new methods for adaptive, knowledge-based learning, such as online incremental feature selection, spiking neural networks, transductive neuro-fuzzy inference, adaptive data and model integration, cellular automata and artificial life systems, particle swarm optimisation, ensembles of evolving systems, and quantum inspired neural networks. New applications to gene and protein interaction modelling, brain data analysis and brain model creation, computational neuro-genetic modelling, adaptive speech, image and multimodal recognition, language modelling, adaptive robotics, modelling dynamic financial and socio-economic systems, and ecological modelling, are covered. An important new feature of the book is the attempt to connect different structural and functional levels of a complex, intelligent system, looking for inspiration from functional relationships in natural systems, such as the genetic and the brain activity.
Evolutionary Synthesis of Pattern Recognition Systems
Evolutionary Synthesis of Pattern Recognition Systems presents novel effective approaches based on evolutionary computational techniques, such as genetic programming (GP), linear genetic programming (LGP), coevolutionary genetic programming (CGP) and genetic algorithms (GA) to automate the synthesis and analysis of object detection and recognition systems. The book’s concepts, principles, and methodologies will enable readers to automatically build robust and flexible systems—in a systematic manner—that can provide human-competitive performance and reduce the cost of designing and maintaining these systems. Its content covers all key aspects of object recognition: object detection, feature selection, feature discovery, object recognition, domain knowledge. Basic knowledge of programming and data structures, and some calculus, is presupposed.ing the book’s novel ideas
Evaluation of Multilingual and Multi-modal Information Retrieval ; 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers
This book covers Multilingual Textual Document Retrieval, Domain-Specifig Information Retrieval, i-CLEF, QA@CLEF, ImageCLEF, CLSR, WebCLEF and GeoCLEF.
Euro-Par 2006 Parallel Processing ; CoreGRID 2006, UNICORE Summit 2006, Petascale Computational Biology and Bioinformatics, Dresden, Germany, August 29-September 1, 2006, Revised Selected Papers
This book contiants Petascale Computational Biology and Bioinformatics.
Essential Renderman
RenderMan has long been associated with top-end film production and is an essential tool for creating many of the effects and images in recent animated films (such as Monsters, Inc., Finding Nemo and The Incredibles). RenderMan is widely available and, with the demand for higher quality images, is now used by computer-based artists at all levels of the graphics industry. Intended to provide a straightforward and easy introduction to the basic techniques involved, this book provides an excellent grounding, enabling readers to confidently move to more advanced texts.
Entertainment computing – ICEC 2007 ; 6th International Conference, Shanghai, China, September 15-17, 2007, Proceedings
This book are organized in topical sections on augmented, virtual and mixed reality, computer games, image processing, mesh and modeling, digital storytelling and interactive systems, sound, music and creative environments, video processing, rendering, computer animation and networks, game based interfaces, as well as robots and cyber pets.
Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems
"Methods of Artificial Intelligence and Intelligent Agents" contains 13 contributions analyzing such areas of AI as fuzzy set theory, predicate logic, neural networks, clustering, data mining and others. It also presents applications of AI as possible solutions for problems like firm bankruptcy, soil erosion, flight control and others. "Information Technology Security" covers three important areas of security engineering in information systems: software security, public key infrastructure and the design of new cryptographic protocols and algorithms. "Biometric Systems" comprises 11 contributions dealing with face picture analysis and recognition systems. This chapter focuses on known methods of biometric problem solution as well as the design of new models.
