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» Learning in Region-Based Image Retrieval
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147
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ICIP
2000
IEEE
16 years 5 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
145
Voted
CVPR
2000
IEEE
16 years 5 months ago
Discriminant-EM Algorithm with Application to Image Retrieval
In Proc. of IEEE Conf. on CVPR'2000, Vol.I, pp.222-227, Hilton Head Island, SC, 2000 In many vision applications, the practice of supervised learning faces several difficulti...
Ying Wu, Qi Tian, Thomas S. Huang
120
Voted
ACCV
2007
Springer
15 years 9 months ago
Combined Object Detection and Segmentation by Using Space-Time Patches
This paper presents a method for classifying the direction of movement and for segmenting objects simultaneously using features of space-time patches. Our approach uses vector quan...
Yasuhiro Murai, Hironobu Fujiyoshi, Takeo Kanade
136
Voted
AMR
2007
Springer
140views Multimedia» more  AMR 2007»
15 years 9 months ago
Learning Distance Functions for Automatic Annotation of Images
This paper gives an overview of recent approaches towards image representation and image similarity computation for content-based image retrieval and automatic image annotation (ca...
Josip Krapac, Frédéric Jurie
122
Voted
SMI
2008
IEEE
126views Image Analysis» more  SMI 2008»
15 years 10 months ago
SHREC'08 entry: Semi-supervised learning for semantic 3D model retrieval
A shape feature by itself is not sufficient for effective 3D model retrieval. Long-lasting semantics shared by a community as well as a short-lived intention of a user determines ...
Akihiro Yamamoto, Masaki Tezuka, Toshiya Shimizu, ...