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Chapter
Foundation of Deep Machine Learning in Neural Networks
This chapter introduces several basic neural network models, which are used as the foundation for the further development of deep machine learning in neural networks. The deep machine learning is a very differ...
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Chapter
Convolutional Neural Networks and Texture Classification
(CNN) model is an instrumental computational model not only in but also in many image and video applications. Similar Cognitron and Neocognitron , CNN can automatically learn the features of data with th...
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Chapter
Texture Features and Image Texture Models
an important phenomenon in many applications of and . Hence, several models for deriving texture properties have been proposed and developed. Although there is no formal definition of image texture in ...
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Chapter
Dimensionality Reduction and Sparse Representation
Image representation is a fundamental issue in signal processing, pattern recognition, and computer vision. An efficient image representation can lead to the development of effective algorithms for the interpr...
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Article
An Image-guided Endoscope System for the Ureter Detection
The ureter injury occasionally happens in the gynecology, abdominal and urinary surgeries. The medical negligence may cause severe problems for the hospital, and mental pressure for the doctors. Furthermore, t...
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Article
An Augmented Reality Endoscope System for Ureter Position Detection
Iatrogenic injury of ureter in the clinical operation may cause the serious complication and kidney damage. To avoid such a medical accident, it is necessary to provide the ureter position information to the d...
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Article
Data-Centric Intelligent Computing
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Article
Credibilistic clustering algorithms via alternating cluster estimation
Credibilistic clustering is a new clustering method using the credibility measure in fuzzy clustering. Zhou et al. (2014) presented the clustering model of credibilistic clustering together with a credibilistic c...
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Chapter and Conference Paper
Bi-MOCK: A Multi-objective Evolutionary Algorithm for Bi-clustering with Automatic Determination of the Number of Bi-clusters
Bi-clustering is one of the main tasks in data mining with many possible applications in bioinformatics, pattern recognition, text mining, just to cite a few. It refers to simultaneously partitioning a data ma...
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Article
Contour propagation using non-uniform cubic B-splines for lung tumor delineation in 4D-CT
Accurate target delineation is a critical step in radiotherapy. In this study, a robust contour propagation method is proposed to help physicians delineate lung tumors in four-dimensional computer tomography (...
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Article
A Novel Endoscope System for Position Detection and Depth Estimation of the Ureter
Iatrogenic injury of ureter occurs occasionally in the clinical laparoscopic surgery. The ureter injury may cause the serious complications and kidney damage. To avoid such an injury, it is necessary to detect...
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Article
Wireless Capsule Endoscopy Video Reduction Based on Camera Motion Estimation
Wireless capsule endoscopy (WCE) is a novel technology aiming for investigating the diseases and abnormalities in small intestine. The major drawback of WCE examination is that it takes a long time to examine ...
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Chapter and Conference Paper
Improving Image Segmentation Algorithms with Differential Evolution
This paper proposes three algorithms based on the K-means, the simple competitive learning (SCL) algorithm, and the fuzzy c-means algorithm with differential evolution algorithm for image classification. Due t...
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Chapter and Conference Paper
The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking
Communication is a fundamental function of life, and it exists in almost all living things: from single-cell bacteria to human beings. Communication, together with competition and cooperation,are...
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Chapter and Conference Paper
A Hybrid Rough K-Means Algorithm and Particle Swarm Optimization for Image Classification
This paper proposes a hybrid rough K-means algorithm for image classification. The rough set theory is used to establish the lower and upper bound for data clustering in the K-means algorithm. Then, the partic...
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Chapter and Conference Paper
Using Ant Colony Optimization and Self-organizing Map for Image Segmentation
In this study, ant colony optimization (ACO) is integrated with the self-organizing map (SOM) for image segmentation. A comparative study with the combination of ACO and Simple Competitive Learning (SCL) is pr...
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Chapter and Conference Paper
Hybridization of the Ant Colony Optimization with the K-Means Algorithm for Clustering
In this paper the novel concept of ACO and its learning mechanism is integrated with the K-means algorithm to solve image clustering problems. The learning mechanism of the proposed algorithm is obtained by us...
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Chapter and Conference Paper
Image Segmentation Using Dynamic Run-Length Coding Technique
In this study, a new segmentation algorithm based on a modified Dynamic Window-based gray-level Run-Length Coding (DW-RLC) applied to neighboring pixels is proposed. The method is applied to gray scale images,...
