Discrete Geometry for Computer Imagery ; 14th IAPR International Conference, DGCI 2008, Lyon, France, April 16-18, 2008. Proceedings
This book constitutes the refereed proceedings of the 14th IAPR TC-18 International Conference on Discrete Geometry for Computer Imagery, DGCI 2008, held in Lyon, France, in April 2008.
Digital watermarking ; 6th International Workshop, IWDW 2007 Guangzhou, China, December 3-5, 2007 Proceedings
This book constitutes the refereed proceedings of the 6th International Workshop, IWDW 2007, held in Guangzhou, China, in December 2007.
Digital Signal Processing : An Experimental Approach
Digital Signal Processing is a mathematically rigorous but accessible treatment of digital signal processing that intertwines basic theoretical techniques with hands-on laboratory instruction. Divided into three parts, the book covers various aspects of the digital signal processing (DSP) "problem".
Digital Mammography ; 9th International Workshop, IWDM 2008 Tucson, AZ, USA, July 20-23, 2008 Proceedings
This volume (5116) of Springer’s Lecture Notes in Computer Science contains the th proceedings of the 9 International Workshop on Digital Mammography (IWDM) which was held July 20 – 23, 2008 in Tucson, AZ in the USA.
Digital Imaging and Communications in Medicine (DICOM) : A Practical Introduction and Survival Guide
This is the first Digital Imaging and Communications in Medicine (DICOM) book to introduce this complex imaging standard from a very practical point of view. It is aimed at a broad audience of radiologists, clinical administrators, information technologists, and digital medicine practitioners.
Digital Image Processing : An Algorithmic Introduction using Java
This modern, self-contained, textbook explains the fundamental algorithms of digital image processing through practical examples and complete Java implementations.
Digital Image Processing
The book offers an integral view of image processing from image acquisition to the extraction of the data of interest. The discussion of the general concepts is supplemented with examples from applications on PC-based image processing systems and ready-to-use implementations of important algorithms. Each chapter now includes exercises that help you to test your understanding, train your skills, and introduce you to real-world image processing tasks. An important part of the exercises is a wealth of interactive computer exercises, which cover all topics of this textbook.
Digital Human Modeling : Trends in Human Algorithms
The emerging information technologies have given rise to new human patterns in terms of both physiological and psychological interactions. Human Algorithms aim to model human forms, interactions, and dynamics in this new context.
Digital Document Processing : Major Directions and Recent Advances
With the advent of the Digital Library initiative, web document processing and biometric aspects of digital document processing, together with new techniques of printed and handwritten Optical Character Recognition (OCR), a good overview of this fast-developing field is invaluable. In this book, all the major and frontier topics in the field of document analysis are brought together into a single volume creating a unique reference source.
Developing bus management system for AIU
To solve the problem of congestion in bus stops for students, members of the administrative and educational people at the Arab International University, an application was designed that allows the user to reserve a seat on the bus. The application provides prior reservation and enters the study time for the user, the application reminds him for the time of his going to the university. The basic functions of the application are designed according to the general analysis, The development of the application used Laravel, flutter frameworks, AI and MySQL database processing technology. The application has accomplished such functions as notification for location. The test of the application is running in good conditions. The use of the application will solve the problem of bus crowding. The efficiency of the platform makes it a very good candidate to be implemented for any person in Arab International University.
Deterministic and statistical methods in Machine Learning ; 1st International Workshop, Sheffield, UK, September 7-10, 2004. Revised Lectures
This book consitutes the refereed proceedings of the First International Workshop on Machine Learning held in Sheffield, UK, in September 2004. The 19 revised full papers presented were carefully reviewed and selected for inclusion in the book. They address all current issues in the rapidly maturing field of machine learning that aims to provide practical methods for data discovery, categorisation and modelling. The particular focus of the workshop was advanced research methods in machine learning and statistical signal processing.
Dendrimer Catalysis
catalytically active dendrimers have emerged as a class of molecular catalysts that has substantially enriched the field of homogeneous (and in part heterogeneous) catalysis. A general survey of transition metal dendrimer catalysts and the way they have developed is followed by in-depth discussions of dendritic transition metal catalysis based on non-covalent catalyst-support interaction and an overview of the rapidly growing field of stereoselective dendrimer catalysis. The development of dendrimer-encapsulated bimetallic nanoparticles has provided the interface with heterogeneous colloid catalysis. As cheaper and readily accessible alternatives to regular dendrimers, hyperbranched polymers are increasingly being used as catalyst platforms. These topics are complemented by a review of metallodendritic exoreptors for the redox recognition of oxo-anions and halides.
Deep structure, singularities, and computer vision ; 1st international workshop, DSSCV 2005, Maastricht, The Netherlands, June 9-10, 2005, revised selected papers
Constitutes the refereed post-proceedings of the First International Workshop on Deep Structure, Singularities, and Computer Vision, DSSCV 2005, held in Maastricht. This book represents in understanding the relation between structural, topological information represented by singularities and metric information of signals, shapes, and colors.
Deep Learning-Based Face Analytics
Provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field.
Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics : Techniques and Applications
Examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever.
Deep Learning to See : Towards New Foundations of Computer Vision
Topics and features: Presents a curiosity-driven approach, posing questions to stimulate readers to design novel computational models of vision Offers a rethinking of computer vision, arguing for an approach based on vision in nature, versus regarding visual signals as collections of images Provides an interdisciplinary commentary, aiming to unify computer vision, machine learning, human vision, and computational neuroscience Serving to inspire and stimulate critical reflection and discussion, yet requiring no prior advanced technical knowledge, the text can naturally be paired with classic textbooks on computer vision to better frame the current state of the art, open problems, and novel potential solutions.
Deep learning methods for converting speech to text = تقنيات التعلم العميق في تحويل الصوت إلى نص
Aims to design and develop a system capable of extracting audio content from films and audio recordings and converting it into text using deep learning techniques. This is done by analyzing audio patterns, extracting sounds and words from the video, and then converting them into written text. Deep learning, a branch of artificial intelligence, is used to accomplish this task. The study also includes comparing different deep learning techniques to determine their effectiveness in this context.
Deep learning architecture and application
As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market).
Deep Learning and its Applications
Presents an introduction to deep learning and various applications of deep learning such as recommendation systems, text recognition, diabetic retinopathy prediction of breast cancer, prediction of epilepsy, sentiment, fake news detection, software defect prediction and protein function prediction.
Data science and analytics ; 5th International conference on recent developments in science, engineering and technology, REDSET 2019, Gurugram, India, November 15–16, 2019, Revised Selected Papers, Part I
This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.



















