Add to ORKGTo improve the performance of content-based image retrieval with relevance feedback by tackling the small-sample problem in learning and retrieval.Doctor of Philosophy (EEE
Abstract—We propose a new relevance feedback approach to achieving high system accuracy for image co...
In this paper, a sub-vector weighting scheme is proposed for the case of small sample in image retri...
Content-based image retrieval has become one of the most active research areas in the past few year...
An image is a symbolic representation; people interpret an image and associate semantics with it bas...
In this paper we describe the current state of the art in relevance feedback as seen from a content-...
We analyze the special structure of the relevance feedback learning problem, focusing particularly o...
User Relevance feedback techniques based on learning methods such as Artificial Neural Networks and ...
The retrieval performance of content-based image retrieval (CBIR) systems is often disappointingly l...
Abstract. We investigate models for content-based image retrieval with relevance feedback, in partic...
In this paper we address several aspects of the learning problem in content-based image retrieval (C...
Abstract- Content-based image retrieval (CBIR) systems have drawn interest from many researchers in ...
High-retrieval precision in content-based image retrieval can be attained by adopting relevance feed...
Relevance feedback is an effective scheme bridging the gap between high-level semantics and low-leve...
Information Retrieval is one of the major research areas in the recent years. There are two kinds of...
After more than 20 years of research on Content-Based Image Retrieval (CBIR), the community is still...
Abstract—We propose a new relevance feedback approach to achieving high system accuracy for image co...
In this paper, a sub-vector weighting scheme is proposed for the case of small sample in image retri...
Content-based image retrieval has become one of the most active research areas in the past few year...
An image is a symbolic representation; people interpret an image and associate semantics with it bas...
In this paper we describe the current state of the art in relevance feedback as seen from a content-...
We analyze the special structure of the relevance feedback learning problem, focusing particularly o...
User Relevance feedback techniques based on learning methods such as Artificial Neural Networks and ...
The retrieval performance of content-based image retrieval (CBIR) systems is often disappointingly l...
Abstract. We investigate models for content-based image retrieval with relevance feedback, in partic...
In this paper we address several aspects of the learning problem in content-based image retrieval (C...
Abstract- Content-based image retrieval (CBIR) systems have drawn interest from many researchers in ...
High-retrieval precision in content-based image retrieval can be attained by adopting relevance feed...
Relevance feedback is an effective scheme bridging the gap between high-level semantics and low-leve...
Information Retrieval is one of the major research areas in the recent years. There are two kinds of...
After more than 20 years of research on Content-Based Image Retrieval (CBIR), the community is still...
Abstract—We propose a new relevance feedback approach to achieving high system accuracy for image co...
In this paper, a sub-vector weighting scheme is proposed for the case of small sample in image retri...
Content-based image retrieval has become one of the most active research areas in the past few year...