The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Boosting in the limit: maximizing the margin of learned ensembles
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Improved Pairwise Coupling Classification with Correcting Classifiers
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Mining Image Features for Efficient Query Processing
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Toward Perception-Based Image Retrieval
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
An Architecture of a Web-Based Collaborative Image Search Engine
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Confidence-based dynamic ensemble for image annotation and semantics discovery
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
A practical SVM-based algorithm for ordinal regression in image retrieval
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Optimal multimodal fusion for multimedia data analysis
Proceedings of the 12th annual ACM international conference on Multimedia
Semantics and feature discovery via confidence-based ensemble
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Classification of coins using an eigenspace approach
Pattern Recognition Letters
SVM in oracle database 10g: removing the barriers to widespread adoption of support vector machines
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Using One-Class and Two-Class SVMs for Multiclass Image Annotation
IEEE Transactions on Knowledge and Data Engineering
EXTENT: fusing context, content, and semantic ontology for photo annotation
Proceedings of the 2nd international workshop on Computer vision meets databases
A decision support system based on support vector machines for diagnosis of the heart valve diseases
Computers in Biology and Medicine
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Scalable landmark recognition using EXTENT
Multimedia Tools and Applications
Review: A new training method for support vector machines: Clustering k-NN support vector machines
Expert Systems with Applications: An International Journal
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
An efficient algorithm for local distance metric learning
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Entropy descriptor for image classification
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Journal of Intelligent Information Systems
A fuzzy set approach for shape-based image annotation
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Fuzzy image labeling by partially supervised shape clustering
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
A framework for incorporating class priors into discriminative classification
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Semi-supervised learning for image annotation based on conditional random fields
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Multi-view learning from imperfect tagging
Proceedings of the 20th ACM international conference on Multimedia
Entropy based image semantic cycle for image classification
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Learning with limited and noisy tagging
Proceedings of the 21st ACM international conference on Multimedia
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We study how the SVM-based binary classifiers can be effectively combined to tackle the multi-class image classification problem. We study several ensemble schemes, including OPC (one per class), PWC (pairwise coupling), and ECOC (error-correction output coding), that aim to achieve good error correction capability through redundancy. To enhance these ensemble schemes' accuracy, we propose methods that on the one hand boost the margins (i.e., confidence) of the SVM-based binary classifiers, and, on the other hand, remove the noise of irrelevant classifiers from class prediction. From empirical study we show that our margin boosting and noise reduction methods lead to higher classification accuracy than ensemble schemes that are solely designed for maximum error correction capability.