A LONG TERM LEARNING SCHEME IN CBIR SYSTEMS BY DEFINING SEMANTIC TEMPLATES USING INFORMATION OF SIMILARITY-REFINEMENT BASED SHORT TERM LEARNING

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RASHEDI E.; NEZAMABADI POUR H.

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Paper Information

Journal: NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ Year:2012 | Volume:9 | Issue:4 Page(s): 203-212

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Title

A LONG TERM LEARNING SCHEME IN CBIR SYSTEMS BY DEFINING SEMANTIC TEMPLATES USING INFORMATION OF SIMILARITY-REFINEMENT BASED SHORT TERM LEARNING

Author(s)

RASHEDI E. | NEZAMABADI POUR H. | Issue Writer Certificate

Keywords

CONTENT BASED IMAGE RETRIEVALQ3

LONG TERM LEARNINGQ3

SHORT TERM LEARNINGQ2

SEMANTIC TEMPLATEQ3

Abstract

In This paper, a new scheme for LONG TERM LEARNING in CBIR systems is proposed. In this scheme, SEMANTIC TEMPLATEs are extracted from information provided through relevance feedback process for short-term learning which use similarity refinement techniques. This information will be used as SEMANTIC TEMPLATEs in future retrieval sessions to improve the precision of the CBIR system. Also, a similarity function is introduced to calculate the similarity between queries and SEMANTIC TEMPLATEs. The proposed method is examined on a database with 10000 color images. The experimental results and comparison with ‘iFind’ method, confirm the effectiveness of the proposed method.

Cites

CONTENT BASED IMAGE RETRIEVAL BY THE FUSION OF SHORT TERM LEARNING METHODS

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APA: Copy

RASHEDI, E., & NEZAMABADI POUR, H.. (2012). A LONG TERM LEARNING SCHEME IN CBIR SYSTEMS BY DEFINING SEMANTIC TEMPLATES USING INFORMATION OF SIMILARITY-REFINEMENT BASED SHORT TERM LEARNING. NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN), 9(4), 203-212. SID. https://sid.ir/paper/53830/en

Vancouver: Copy

RASHEDI E., NEZAMABADI POUR H.. A LONG TERM LEARNING SCHEME IN CBIR SYSTEMS BY DEFINING SEMANTIC TEMPLATES USING INFORMATION OF SIMILARITY-REFINEMENT BASED SHORT TERM LEARNING. NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN)[Internet]. 2012;9(4):203-212. Available from: https://sid.ir/paper/53830/en

IEEE: Copy

E. RASHEDI, and H. NEZAMABADI POUR, “A LONG TERM LEARNING SCHEME IN CBIR SYSTEMS BY DEFINING SEMANTIC TEMPLATES USING INFORMATION OF SIMILARITY-REFINEMENT BASED SHORT TERM LEARNING,” NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN), vol. 9, no. 4, pp. 203–212, 2012, [Online]. Available: https://sid.ir/paper/53830/en

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