[1] Liu Y., Zhang D., Lu G., and Ma W., “A survey of content-based image retrieval with high-level semantics,” Pattern Recognition, 40: 262-282, 2006, https://doi.org/10.1016/j.patcog.2006.04.045.
[2] Ghosh N., Agrawal S., and Motwani M., “A survey of feature extraction for content-based image retrieval system,” Proceedings of International Conference on Recent Advancement on Computer and Communication, 34: 305-313, 2018, https://doi.org/10.1007/978-981-10-8198-9_32.
[3] Rui Y., Huang T. S., and Change S. F., “Image Retrieval: Current Techniques, Promising Directions and Open Issues,” Journal of Visual Communication and Image Representation and Image Representation, 10: 39-62, 1999, https://doi.org/10.1006/jvci.1999.0413.
[4] Datta R., Joshi D., Li Z., and Wang J. Z., “Image Retrieval: Ideas, Influences, and Trends of the New Age,” ACM Computing Survey, 40: 1-60, 2008, https://doi.org/10.1145/1348246.1348248.
[5] Long F., Zhang H., and Feng D. D., Fundamentals of Content-Based Image Retrieval, Signals and Communication Technology. Springer, 2003, https://doi.org/10.1007/978-3-662-05300-3_1.
[6] Li X., Chen S.C., Shyu M. L., and Furht B., “Image Retrieval by color, Texture, and Spatial Information,” in 8th International Conference on Distributed Multimedia Systems, California , USA: 8, 159-152, 2002.
[7] Muwei J., Junyu D., and Ruichun T., “Image Combining Color, Texture and Region with Objects of user’s Interest for Content-Based Image Retrieval,” 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, IEEE Computer Society, 2007, https://doi.org/10.1109/SNPD.2007.104.
[8] H. Qazanfari, Hassanpour H., and K. Qazanfari, “A short-term learning framework based on relevance feedback for content-based image retrieval,” 2017 3rd Iranian Conference on Intelligent Systems and Signal Processing (ICSPIS), Shahrood, 136-140, 2017.
[9] Quynh D. T., Nguyen H. Q., and Son A. H., “Image Retrieval Uses SVM-Based Relevant Feedback for Imbalance and Small Training Set,” IEEE-RIVF International Conference on Computing and Communication Technologies, IEEE, 1-6, 2019.
[10] Badrinarayanan V., Kendall A., and Cipolla R., “Segnet: A deep convolutional encoder-decoder architecture for image segmentation,” IEEE transactions on pattern analysis and machine intelligence, 39: 2481-2495, 2017, https://doi.org/10.1109/TPAMI.2016.2644615.
[11] Bose S., Pal A., Mallick J., Kumar S., and Rudra P., “A Hybrid Approach for Improved Content-based Image Retrieval using Segmentation,” arXiv preprint arXiv: 1502.03215, 2015.
[12] Sardari M., Monadjemi A., and Jamshidi K., “A concept based model for image retrieval systems,” Computers and Electrical Engineering, 46: 303-313, 2015, https://doi.org/10.1016/j.compeleceng.2015.06.018.
[13] Sardari M., Monadjemi A., and Jamshidi K., “A semantic model for general purpose content-based image retrieval systems,” Computers and Electrical Engineering, 40: 2062-2071, 2017, https://doi.org/10.1016/j.compeleceng.2014.07.008.
[14] Dayma A., Shrivastava A., Saxena A.K., and Manoria M., “Support Vector Machine (Linear Kernel) and Interactive Genetic Algorithm-Based Content Image Retrieval Technique,” Proceedings of International Conference on Recent Advancement on Computer and Communication, Springer, Singapore, 34: 151-159, 2018, https://doi.org/10.1007/978-981-10-8198-9_16.
[15] Huneiti A. and Maisa D., “Content-based image retrieval using SOM and DWT,” Journal of software Engineering and Applications, 8: 51-61, 2015, https://doi.org/10.4236/jsea.2015.82007.
[16] Carneiro G., Chan A. B., Moreno P. J., and Vasconcelos N., “Supervised learning of semantic classes for image annotation and retrieval,” IEEE transactions on pattern analysis and machine intelligence, 29: 394-410, 2007, https://doi.org/10.1109/TPAMI.2007.61
[17] Yang W., Yin X., and Xia G. S., “Learning high-level features for satellite image classification with limited labeled samples,” IEEE Transactions on Geoscience and Remote Sensing, 53: 4472-4482, 2015, https://doi.org/10.1109/TGRS.2015.2400449.
[18] Heller K. A. and Ghahramani Z., “A simple Bayesian framework for content-based image retrieval,” in Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, 2110-2117, 2006, https://doi.org/10.1109/CVPR.2006.41.
[19] Bose S., Pal A., Mallick J., Kumar S., and Rudra P., “A Hybrid Approach for Improved Content-based Image Retrieval using Segmentation,” arXiv preprint arXiv: 1502.03215. 2015.
[20] Long J., Shelhamer E., and Darrell T., “Fully convolutional networks for semantic segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3431-3440, 2015, https://doi.org/10.1109/CVPR.2015.7298965.
[21] Meng X., An Y., He J., Zhuo Z., Wu H., and Gao X., “Similar image retrieval only using one image,” Optik-International Journal for Light and Electron Optics, 127: 141-144, 2016, https://doi.org/10.1016/j.ijleo.2015.10.041.
[22] Xu Y. Y., “Multiple-instance learning based decision neural networks for image retrieval and classification,” Neurocomputing, 171: 826-836, 2016, https://doi.org/10.1016/j.neucom.2015.07.024.
[23] Thilagam M. and Arunish K., “Content-based image retrieval techniques: A review,” in International Conference on Intelligent Computing and Communication for Smart World (I2C2SW), 106-110, 2018.
[24] Kastner S. and Ungerleider L. G., “The neural basis of biased competition in human visual cortex,” Neuropsychologia, 39: 1263-1276, 2001, https://doi.org/10.1016/s0028-3932(01)00116-6.
[25] رزاقزاده ش.، نوروزیکیوی پ.، پناهی ب.، «الگوریتم ترکیبی مبتنی بر معماری گوسیپ با استفاده از SVM برای زمانبندی وظایف در رایانش ابری»، مجله محاسبات نرم، جلد 9، شماره 2، ص. 84-93، 1399، https://doi.org/10.22052/SCJ.2021.242822.0.
[26] ویسی ه.، قایدشرف ح.، ابراهیمی م.، «بهبود کارایی الگوریتمهای یادگیری ماشین در تشخیص بیماریهای قلبی با بهینهسازی دادهها و ویژگیها»، مجله محاسبات نرم، جلد 8، شماره 1، ص. 70-85، 1398، https://doi.org/10.22052/8.1.70.
[27] وثیقیذاکر ا.، جلیلی س.، «پیشبینی ژنهای بیماری با استفاده از دستهبند تککلاسی ماشین بردار پشتیبان»، مجله محاسبات نرم، جلد 4، شماره 1، ص. 74-83، 1394، https://doi.org/20.1001.1.23223707.1394.4.1.60.8.
[28] Hsu C. and Lin C., “A comparison of methods for multiclass support vector machines,” IEEE transactions on Neural Networks, 13: 415-425, 2002, https://doi.org/10.1109/72.991427.
[29] Dataset: http://smartcbir.nph-co.ir/datasets.php, latest accessed 2020/06/21.
[30] Kaur S. and Aggarwal D., “Image Content Based Retrieval System using Cosine Similarity for Skin Disease Images,” Advances in Computer Science: an International Journal, 2: 89-95, 2013.
[31] Ajam A., Forghani M., AlyanNezhadi M. M., Qazanfari H., and Amiri Z., “Content-based Image Retrieval Using Color Difference Histogram in Image Textures,” 5th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Shahrood, Iran, 5: 1-6, 2019, https://doi.org/10.1109/ICSPIS48872.2019.9066062.
[32] Alyan-Nezhadi M., Qazanfari H., Ajam A., and Amiri Z., “Content-based Image Retrieval Considering Colour Difference Histogram of Image Texture and Edge Orientation,” International Journal of Engineering, 33: 949-958, 2020, https://doi.org/10.5829/IJE.2020.33.05B.28.