Mendeley
TY  _  JOUR
ID  -  139604202215106862
TI  -  Content Based Image Retrieval by the Fusion of Short Term Learning Methods
JO  -  Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran
JA  -  ES
LA  -  fa
SN  -  16823745
AU  -  Bagheri B.
AU  -  Pourmahyabadi M.
AU  -  nezam nezam
AD  -  دانشگاه شهید باهنر کرمان
AD  -  دانشگاه شهید باهنر کرمان
AD  -  
Y1  -  2020
PY  -  2020
VL  -  4
IS  -  
SP  -  101
EP  -  111
KW  -  Content based image retrieval
relevance feedback
semantic gap
fusion
short-term learning
DO  -  
N2  -  Content based image retrieval (CBIR) contains a set of techniques to process the visual features of a query image, in order to retrieve images semantically similar to it, in a database. To improve the performance of image retrieval systems, relevance feedback tool can be used. In this research, to increase the effectiveness of the image retrieval systems, the fusion of two (multiple) short term learning methods based on relevance feedback is proposed. In the proposed method, fusion is performed in three levels: fusion in ranks, fusion in retrieved images, and fusion in similarities. To evaluate the performance of the proposed method, a CBIR system with 10000 images of 82 different semantic groups is employed. The experimental results confirm the superior of suggested method in terms of retrieval precision.
UR  - rimag.ir/en/Article/28145
L1  - rimag.ir/en/Article/Download/28145
ER  -  
