Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
On image auto-annotation with latent space models
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Effective automatic image annotation via a coherent language model and active learning
Proceedings of the 12th annual ACM international conference on Multimedia
Image annotations by combining multiple evidence & wordNet
Proceedings of the 13th annual ACM international conference on Multimedia
Graph based multi-modality learning
Proceedings of the 13th annual ACM international conference on Multimedia
Correlated Label Propagation with Application to Multi-label Learning
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
An adaptive graph model for automatic image annotation
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
International Journal of Computer Vision
A New Baseline for Image Annotation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Automatic image annotation using visual content and folksonomies
Multimedia Tools and Applications
IEEE Transactions on Multimedia - Special issue on integration of context and content
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Image Processing
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With the rapid development of Internet technologies, distance education has become a popular educational mode. In this paper, the authors propose an online image automatic annotation distance education system, which could effectively help children learn interrelations between image content and corresponding keywords. Image automatic annotation is a significant problem in image retrieval and image understanding. The authors propose a K-Nearest Neighbors Relevance model, which combines KNN method with relevance models. The model solves the problems of high computational complexity and annotation results affected by irrelevant training images when joint generation probabilities between visual areas and keywords are calculated. The authors also propose a multi-scale windows method and nearest-neighbors weighting method based on rank-weighting and distance-weighting. Experiments conducted on Corel datasets verify that the K-Nearest Neighbors Relevance model is quite effective.