Machine Learning
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
On the Accuracy of Meta-learning for Scalable Data Mining
Journal of Intelligent Information Systems
Communications of the ACM
Visual information retrieval from large distributed online repositories
Communications of the ACM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
PicSOM—content-based image retrieval with self-organizing maps
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Evaluating a content based image retrieval system
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Perspectives on Content-Based Multimedia Systems
Perspectives on Content-Based Multimedia Systems
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Unifying Keywords and Visual Contents in Image Retrieval
IEEE MultiMedia
SemQuery: Semantic Clustering and Querying on Heterogeneous Features for Visual Data
IEEE Transactions on Knowledge and Data Engineering
Indexing Flower Patent Images Using Domain Knowledge
IEEE Intelligent Systems
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Applications of Support Vector Machines for Pattern Recognition: A Survey
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Indoor-Outdoor Image Classification
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Computationally Efficient Approach to Indoor/Outdoor Scene Classification
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Search strategies in content-based image retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Experimental result analysis for a generative probabilistic image retrieval model
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Image classification using hybrid neural networks
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Wavelet Based Texture Classification
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
The Journal of Machine Learning Research
Content-based image classification using a neural network
Pattern Recognition Letters
Qualitative evaluation of automatic assignment of keywords to images
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
Web Search: Public Searching of the Web (Information Science and Knowledge Management)
Web Search: Public Searching of the Web (Information Science and Knowledge Management)
Image classification for content-based indexing
IEEE Transactions on Image Processing
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Automatic index construction for multimedia digital libraries
Information Processing and Management: an International Journal
Image annotation by incorporating word correlations into multi-class SVM
ICNC'09 Proceedings of the 5th international conference on Natural computation
An HMM-SVM-based automatic image annotation approach
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
| Hi-index | 0.00 |
Many users of image retrieval systems would prefer to express initial queries using keywords. However, manual keyword indexing is very time-consuming. Therefore, a content-based image retrieval system which can automatically assign keywords to images would be very attractive. Unfortunately, it has proved very challenging to build such systems, except where either the image domain is restricted or the keywords relate only to low-level concepts such as color. This article presents a novel image indexing and classification system, called CLAIRE (CLAssifying Images for REtrieval), composed of one image processing module and three modules of support vector machines for color, texture, and high-level concept classification for keyword assignment. The experimental prototype system described here assigns up to five keywords selected from a controlled vocabulary of 60 terms to each image. The system is trained offline by 1639 examples from the Corel stock photo library. For evaluation, five judges reviewed a sample of 800 unknown images to identify which automatically assigned keywords were actually relevant to the image. The system proved to have an 80% probability to assign at least one relevant keyword to an image.