@article{MAKHILLAJIT20181726718,
    title = {Content-Based Image Retrieval Based on High Level Labels},
    journal = {Asian Journal of Information Technology},
    volume = {17},
    number = {2},
    pages = {98-113},
    year = {2018},
    issn = {1682-3915},
    doi = {ajit.2018.98.113},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2018.98.113},
    author = {Nasibeh Esmaeili and},
    keywords = {ST,image retrieval,learning,lung,queries,allocated},
    abstract = {Text-based and content-based retrieval are considered as two main approaches of the image-based
retrieval. Challenges faced by both approaches direct researchers toward combined approaches and
semi-automatic retrieval by the collaboration of the user in the cycle of retrieval specifically in the field of
medical issues. Therefore, in this study, a system of image retrieval is introduced which provides user with two
types of query based on keywords and images. After retrieval of the initial results, proposed system performs
retrieval operation in a semantic manner and semi-automatically using feedbacks received from the user and
high level semantic tags allocated to the images. By means of a hierarchical ST and a type of learning by user
feedbacks, system is able to respond to diverse queries in the field of image retrieval. According to tests,
proposed system is of acceptable precision.}
    }