Welcome to our book review site www.go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
International Conference on Advances in Pattern Recognition
International Conference on Advances in Pattern Recognition (ICAPR 98) at Plymouth represents an important meeting for advanced research in pattern recognition. There is considerable interest in the areas of image processing, medical imaging, speech recognition, document analysis and character recognition, fuzzy data analysis and neural networks. ICAPR 98 is aimed at providing an international platform for invited research in this multi-disciplinary area. It is expected that the conference will grow in future years to include more research contributions that detail state-of the-art research in pattern recognition. ICAPR 98 attracted contributions from different countries of the highest quali...
Computer Analysis of Images and Patterns
This volume presents the articles accepted for the 8th International Conference on Computer Analysis of Images and Patterns (CAIP’99), held in Ljubljana, Slovenia, 1{3 September 1999. The CAIP series of conferences started 14 years ago in Berlin. The series served initially as a forum for meetings between sci- tists from Western and Eastern-bloc countries. Political circumstances have changed dramatically since the inception of the conference and such contacts are fortunately no longer subject to abstrade. While CAIP conferences are still rooted in Central Europe, they now attract participants from all over the world. We received 120 submissions, which went through a thorough double blind ...
Computational Neurogenetic Modeling
Computational Neurogenetic Modeling is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM). CNGM is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge from various scientific disciplines, such as computer and information science, neuroscience and cognitive science, genetics and molecular biology, as well as engineering.
Complex Systems Science in Biomedicine
Complex Systems Science in Biomedicine Thomas S. Deisboeck and J. Yasha Kresh Complex Systems Science in Biomedicine covers the emerging field of systems science involving the application of physics, mathematics, engineering and computational methods and techniques to the study of biomedicine including nonlinear dynamics at the molecular, cellular, multi-cellular tissue, and organismic level. With all chapters helmed by leading scientists in the field, Complex Systems Science in Biomedicine's goal is to offer its audience a timely compendium of the ongoing research directed to the understanding of biological processes as whole systems instead of as isolated component parts. In Parts I & II, ...
Handbook of Biomedical Image Analysis
Our goal is to develop automated methods for the segmentation of thr- dimensional biomedical images. Here, we describe the segmentation of c- focal microscopy images of bee brains (20 individuals) by registration to one or several atlas images. Registration is performed by a highly parallel imp- mentation of an entropy-based nonrigid registration algorithm using B-spline transformations. We present and evaluate different methods to solve the cor- spondence problem in atlas based registration. An image can be segmented by registering it to an individual atlas, an average atlas, or multiple atlases. When registering to multiple atlases, combining the individual segmentations into a ?nalsegment...
Advances in Pattern Recognition - ICAPR 2001
The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples o...
3D Printing: Applications in Medicine and Surgery
New technologies in 3D printing offer innovative capabilities in surgery, biomedical engineering and nanotechnology. This hot topic title synthesizes the most up-to-date information on 3D printing and provides guidance on the optimal application in today's surgical practice, from evaluation in the technology, patient education uses, to ethics and intellectual property, through to virtual reality and future opportunities. Includes expert guidance on the challenges, opportunities, and limitations of 3D printing in the field of surgery. Covers patient and surgical education, ethics and intellectual property, quality and safety, 3D printing as it relates to nanotechnology, tissue engineering, virtual augmented reality, and more. Consolidates today's available information in this rapidly growing area into a single convenient resource.
Artificial Intelligence in e-Health Framework, Volume 1
Artificial Intelligence in e-health Framework, Volume One: AI, Classification, Wearable Devices, and Computer-Aided Diagnosis presents a variety of AI techniques and applications for solving issues in the healthcare industry. As Artificial Intelligence is increasingly incorporated into medical systems and methods, it is critical to understand the formulations and basics of machine and deep learning as well as how to implement these advances into practice. This book specifically explores Artificial Intelligence developments in disease diagnosis, health monitoring, medical image recognition, and diagnostics, as well as e-health records management.This is a valuable resource for health professionals, scientists, researchers, students, and all who wish to broaden their knowledge in this advancing technology. - Provides an in-depth introduction to Artificial Intelligence in e-health framework - Reviews theoretical and application information to develop understanding of AI advances in diagnostics, health monitoring, and records management - Discusses advanced AI techniques in both machine learning and deep learning for solving healthcare industry issues
