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KES
2005
Springer
12 years 5 months ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
ICMCS
2007
IEEE
126views Multimedia» more  ICMCS 2007»
12 years 5 months ago
Learning from Relevance Feedback Sessions using a K-Nearest-Neighbor-Based Semantic Repository
This paper introduces a flexible learning approach for image retrieval with relevance feedback. A semantic repository is constructed offline by applying the k-nearest-neighborbase...
Matthew Royal, Ran Chang, Xiaojun Qi
CVPR
2001
IEEE
13 years 1 months ago
Learning Similarity Measure for Natural Image Retrieval with Relevance Feedback
A new scheme of learning similarity measure is proposed for content-based image retrieval (CBIR). It learns a boundary that separates the images in the database into two parts. Im...
Guodong Guo, Anil K. Jain, Wei-Ying Ma, HongJiang ...
SIGIR
1999
ACM
12 years 3 months ago
Relevance Feedback Retrieval of Time Series Data
There has been much recent interest in retrieval of time series data. Earlier work has used a fixed similarity metric (e.g., Euclidean distance) to determine the similarity betwee...
Eamonn J. Keogh, Michael J. Pazzani
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
12 years 4 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
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