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CISST
2004
164views Hardware» more  CISST 2004»
13 years 9 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp
PAKDD
2009
ACM
263views Data Mining» more  PAKDD 2009»
14 years 2 months ago
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap b...
Xin Chen, Xiaohua Hu, Xiajiong Shen
MTA
2000
165views more  MTA 2000»
13 years 7 months ago
Approximating Content-Based Object-Level Image Retrieval
Object-level image retrieval is an active area of research. Given an image, a human observerdoesnot see randomdots of colors. Rather,he she observesfamiliarobjectsin the image. The...
Wynne Hsu, Tat-Seng Chua, Hung Keng Pung
ECIR
2004
Springer
13 years 9 months ago
NNk Networks for Content-Based Image Retrieval
Abstract. This paper describes a novel interaction technique to support content-based image search in large image collections. The idea is to represent each image as a vertex in a ...
Daniel Heesch, Stefan M. Rüger
ICVGIP
2004
13 years 9 months ago
Content Based Image Retrieval with Multiresolution Salient Points
This paper presents a robust technique for Content Based Image Retrieval (CBIR) using salient points of an image. The salient points are extracted from different levels of the uns...
Minakshi Banerjee, Malay K. Kundu