The nature of statistical learning theory
The nature of statistical learning theory
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
The Evolving Tree—A Novel Self-Organizing Network for Data Analysis
Neural Processing Letters
Expert system based on artificial neural networks for content-based image retrieval
Expert Systems with Applications: An International Journal
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
IEEE Transactions on Image Processing
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Automated diagnosis of sewer pipe defects based on machine learning approaches
Expert Systems with Applications: An International Journal
Characteristics analysis for small data set learning and the comparison of classification methods
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Segmenting ideal morphologies of sewer pipe defects on CCTV images for automated diagnosis
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
The characteristics of learning in limited data and the comparative assessment of learning methods
WSEAS Transactions on Information Science and Applications
Multimedia Tools and Applications
The forecasting model based on wavelet ν-support vector machine
Expert Systems with Applications: An International Journal
Data attribute reduction using binary conversion
WSEAS Transactions on Computers
Image compression scheme based on curvelet transform and support vector machine
Expert Systems with Applications: An International Journal
Image and Vision Computing
Predicting high-tech equipment fabrication cost with a novel evolutionary SVM inference model
Expert Systems with Applications: An International Journal
Analyzing ECG for cardiac arrhythmia using cluster analysis
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
Fast and accurate image classification is becoming one of the key requirements in content-based image retrieval (CBIR). Various methods including artificial neural networks have been used to classify a large image database efficiently and shown to be highly successful in this application area. This paper presents a one-class support vector machine (SVM) based classification method that can categorize a large image database efficiently by color and text content for content-based image retrieval. In order to evaluate one-class SVMs, this paper examines the performance of the proposed method by comparing it with that of multilayer perception, one of the artificial neural network techniques, based on real real-world image data. The experiment shows that the results of one-class SVMs outperform those of ANNs.