automatically segments the dominant foreground region, consisting of the semantic concept of the image, such as elephants, roses and does the semantic learning, is proposed. Approach: The system segments an image into different regions and finds the dominant foreground region in it, which is the semantic concept of that image. Then it extracts the low-level features of that dominant foreground region. The Support Vector Machine-Binary Decision Tree (SVM-BDT) is used for semantic learnin
A learning approach to knowledge-assisted image analysis and classification is proposed that combin...
[[abstract]]Traditional content-based image retrieval (CBIR) systems often fail to fulfill a user’s ...
An object-oriented approach for semantic-based image retrieval is presented. The goal is to identify...
Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a r...
A structured vocabulary of terms, such as a textual thesaurus, provides a way to conceptually descri...
[[abstract]]This thesis focuses on issues of region-based image retrieval, which employs image regio...
Image retrieval has lagged far behind text retrieval despite more than two decades of intensive rese...
An image retrieval methodology suited for search in large collections of heterogeneous images is pre...
In this paper, a learning approach to semantic image analysis and classification is proposed that co...
Semantic extraction for images is an urgent problem and is applied in many different semantic retrie...
The accumulation of large collections of digital images has created the need for efficient and intel...
In this study, a content based image retrieval (CBIR) system to query the objects in an image databa...
This paper proposes an image retrieval system scheme based on salient region of interest. In our ret...
Image retrieval has lagged far behind text retrieval despite more than two decades of intensive rese...
This book presents a novel image representation that allows to access natural scenes by local semant...
A learning approach to knowledge-assisted image analysis and classification is proposed that combin...
[[abstract]]Traditional content-based image retrieval (CBIR) systems often fail to fulfill a user’s ...
An object-oriented approach for semantic-based image retrieval is presented. The goal is to identify...
Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a r...
A structured vocabulary of terms, such as a textual thesaurus, provides a way to conceptually descri...
[[abstract]]This thesis focuses on issues of region-based image retrieval, which employs image regio...
Image retrieval has lagged far behind text retrieval despite more than two decades of intensive rese...
An image retrieval methodology suited for search in large collections of heterogeneous images is pre...
In this paper, a learning approach to semantic image analysis and classification is proposed that co...
Semantic extraction for images is an urgent problem and is applied in many different semantic retrie...
The accumulation of large collections of digital images has created the need for efficient and intel...
In this study, a content based image retrieval (CBIR) system to query the objects in an image databa...
This paper proposes an image retrieval system scheme based on salient region of interest. In our ret...
Image retrieval has lagged far behind text retrieval despite more than two decades of intensive rese...
This book presents a novel image representation that allows to access natural scenes by local semant...
A learning approach to knowledge-assisted image analysis and classification is proposed that combin...
[[abstract]]Traditional content-based image retrieval (CBIR) systems often fail to fulfill a user’s ...
An object-oriented approach for semantic-based image retrieval is presented. The goal is to identify...