Content-based query of image databases: inspirations from text retrieval
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Self-Organizing Maps
Implementing Relevance Feedback as Convolutions of Local Neighborhoods on Self-Organizing Maps
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
MPEG-7 Descriptors in Content-Based Image Retrieval with PicSOM System
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
PicSOM-self-organizing image retrieval with MPEG-7 content descriptors
IEEE Transactions on Neural Networks
Class distribution on SOM surfaces for feature extraction and object retrieval
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Creative Industrial Design and Computer-Based Image Retrieval: The Role of Aesthetics and Affect
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
The state of the art in image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
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Content-based image retrieval (CBIR) addresses the problem of assisting a user to retrieve images from unannotated databases, based on features that can be automatically derived from the images. Today, there exists several CBIR systems based on different methods. Only few attemps to benchmark these have been made, although the usefulness of benchmarking is undeniable in the development of different algorithms. In this paper we publish our benchmarking results of two CBIR systems with different implementation methods. The CBIR systems in question are GIFT (University of Geneva) and PicSOM (Helsinki University of Technology). The results clearly show that our PicSOM system, which we earlier have not been able to benchmark against other CBIR systems, comes off well in the comparison. Also, the results indicate that tests based on a single ground truth class are not enough for fair system comparisons.