یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references.
یادداشتهای مربوط به مندرجات
متن يادداشت
Intro; Foreword; Preface; Acknowledgements; Contents; About the Editors; Abbreviations; Knowledge Processing in Specific Domains; 1 Probabilistic Graphical Models for Medical Image Mining Challenges of New Generation; Abstract; 1 Introduction; 1.1 Image Mining Challenge; 1.2 Probabilistic Graphical Models; 2 Machine Learning Methods in a Medical Context; 2.1 Image Mining Challenges; 3 Medical Image Mining Applications; 3.1 Multiview Feature Representation with MR Imaging; 3.2 Learning and Estimating Respiratory Motion from 4D CT Lung Images.
متن يادداشت
1.2 Baker's Taxonomy2 Problem Domain: Predicting Student Course Outcome at an Early Stage; 2.1 Description and Selection of Dataset; 2.2 Introduction to Classification Technique; 2.2.1 Types of Classification Techniques; 2.2.2 Solving a Classification Problem; 2.2.3 Classification Accuracy; 2.3 Instance-Based Learning; 3 Experimentation and Results; 3.1 Implementation of Single Instance Learning Classification Algorithm; 3.1.1 Rule-Based Algorithms; 3.1.2 Tree-Based Algorithms; 3.1.3 Naïve Bayes Algorithms; 3.1.4 Comparison of Single Instance Learning Algorithms.
متن يادداشت
2.4 Drawbacks of Existing Pipeline Models2.5 Image Analysis and Processing Model of a Pipeline; 2.6 Characteristics of Image Analysis Model; 2.7 Implementation of Digitized Camera with Fiber Optic Cable; 2.8 Pipeline Evaluation; 2.9 Fiber Optic Cable; 3 Image Detection Techniques; 3.1 Gate Turn-Off Thyristors; 3.2 High-Frequency Filter; 3.3 Image Analysis Using Bitmaps; 3.4 Methods to Identify Hidden Structures in an Image; 3.5 Filtration of an Image; 3.6 Characteristics of Cluster Algorithm Model; 3.7 K-Means Algorithm; 4 Morphological Image Processing System.
متن يادداشت
3.3 Hierarchical Parsing in Medical Images Using Machine Learning Technologies [41]3.4 Anatomy Landmark Detection [41]; 3.5 Machine Learning in Brain Imaging [41]; 3.6 A Connectome-Based and Machine Learning Study [41]; 4 Limitations with Medical Images; 4.1 Future Guidelines; 5 Conclusion; References; 2 Pipeline Crack Detection Using Mathematical Morphological Operator; Abstract; 1 Introduction; 1.1 Image Analysis and Processing; 1.2 Image Coordinates; 2 Pipeline; 2.1 Pipeline Design; 2.2 Causes for Pipeline Damage; 2.3 Pipelines Monitoring-Smart Pigs.
متن يادداشت
4.1 Implementation of the Operator Tool4.1.1 Design of the Algorithm; 4.2 Analysis with the Bitmap Set; 4.2.1 Data Gathering Procedure; 4.3 Mode of Analysis-Detection of the Crack with the Morphological Operator; 4.3.1 Types: Erosion and Corrosion; 4.3.2 Opening and Closing Techniques; 4.4 Proposed Method to Implement the Image Analysis Model; 5 Edge Detection of an Image; 5.1 Methods to Detect Edge Defects; 5.1.1 Smoothing of the Detected Image; 6 Conclusion; References; 3 Efficiency of Multi-instance Learning in Educational Data Mining; Abstract; 1 Introduction; 1.1 Educational Applications.
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
This book highlights technical advances in knowledge management and their applications across a diverse range of domains. It explores the applications of knowledge computing methodologies in image processing, pattern recognition, health care and industrial contexts. The chapters also examine the knowledge engineering process involved in information management. Given its interdisciplinary nature, the book covers methods for identifying and acquiring valid, potentially useful knowledge sources. The ideas presented in the respective chapters illustrate how to effectively apply the perspectives of knowledge computing in specialized domains.