{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T19:00:48Z","timestamp":1784833248770,"version":"3.55.0"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s10586-026-06086-w","type":"journal-article","created":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T07:22:08Z","timestamp":1780384928000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A content-based image retrieval approach utilizing optimized intermediate layer features"],"prefix":"10.1007","volume":"29","author":[{"given":"Sunita","family":"Rani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shalini","family":"Batra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geeta","family":"Kasana","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,1]]},"reference":[{"key":"6086_CR1","doi-asserted-by":"publisher","unstructured":"Tianyu, Z., Zhenjiang, M., Jianhu, Z.: Combining cnn with hand-crafted features for image classification, in: 2018 14th IEEE International Conference on Signal Processing (ICSP), 2018, pp. 554\u2013557. https:\/\/doi.org\/10.1109\/ICSP.2018.8652428","DOI":"10.1109\/ICSP.2018.8652428"},{"key":"6086_CR2","doi-asserted-by":"crossref","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 91\u2013110 (2004)","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"issue":"3","key":"6086_CR3","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","volume":"110","author":"H Bay","year":"2008","unstructured":"Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (surf). Computer Vision and Image Understanding 110(3), 346\u2013359 (2008). https:\/\/doi.org\/10.1016\/j.cviu.2007.09.014","journal-title":"Computer Vision and Image Understanding"},{"issue":"12","key":"6086_CR4","doi-asserted-by":"publisher","first-page":"1349","DOI":"10.1109\/34.895972","volume":"22","author":"A Smeulders","year":"2000","unstructured":"Smeulders, A., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell. 22(12), 1349\u20131380 (2000). https:\/\/doi.org\/10.1109\/34.895972","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"6086_CR5","doi-asserted-by":"publisher","first-page":"2021","DOI":"10.14569\/IJACSA.2021.0120723","volume":"12","author":"A Ahmed","year":"2021","unstructured":"Ahmed, A.: Pre-trained cnns models for content based image retrieval. Int. J. Adv. Comput. Sci. Appl. 12, 2021 (2021). https:\/\/doi.org\/10.14569\/IJACSA.2021.0120723","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"issue":"3","key":"6086_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3470568","volume":"2","author":"S Maji","year":"2021","unstructured":"Maji, S., Bose, S.: CBIR using features derived by deep learning. ACM\/IMS Trans. Data Sci. 2(3), 1\u201324 (2021). https:\/\/doi.org\/10.1145\/3470568","journal-title":"ACM\/IMS Trans. Data Sci."},{"key":"6086_CR7","unstructured":"Chen, W.., Liu, Y., Wang, W., Bakker, E.\u00a0M., Georgiou, T., Fieguth, P.\u00a0W., Liu, L., Lew, M.\u00a0S.: Deep image retrieval: a survey (2021). arXiv:2101.11282"},{"issue":"5","key":"6086_CR8","doi-asserted-by":"publisher","first-page":"2687","DOI":"10.1109\/TCSVT.2021.3080920","volume":"32","author":"SR Dubey","year":"2022","unstructured":"Dubey, S.R.: A decade survey of content based image retrieval using deep learning. IEEE Trans. Circuits Syst. Video Technol. 32(5), 2687\u20132704 (2022). https:\/\/doi.org\/10.1109\/TCSVT.2021.3080920","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"1","key":"6086_CR9","doi-asserted-by":"publisher","first-page":"012028","DOI":"10.1088\/1742-6596\/2327\/1\/012028","volume":"2327","author":"S Kumar","year":"2022","unstructured":"Kumar, S., Singh, M.K., Mishra, M.K.: Improve content-based image retrieval using deep learning model. J. Phys: Conf. Ser. 2327(1), 012028 (2022). https:\/\/doi.org\/10.1088\/1742-6596\/2327\/1\/012028","journal-title":"J. Phys: Conf. Ser."},{"key":"6086_CR10","first-page":"251","volume":"9","author":"S Kopparthi","year":"2020","unstructured":"Kopparthi, S., Nynalasetti, K.K.R.: Content based image retrieval using deep learning technique with distance measures. Sci. Technol. Human Values 9, 251\u2013261 (2020)","journal-title":"Sci. Technol. Human Values"},{"key":"6086_CR11","doi-asserted-by":"publisher","unstructured":"Abdel-Nabi, H., Al-Naymat, G., Awajan, A.: Content based image retrieval approach using deep learning, in: 2019 2nd International Conference on new Trends in Computing Sciences (ICTCS), 2019, pp. 1\u20138. https:\/\/doi.org\/10.1109\/ICTCS.2019.8923042","DOI":"10.1109\/ICTCS.2019.8923042"},{"key":"6086_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/app13074581","author":"S Sikandar","year":"2023","unstructured":"Sikandar, S., Mahum, R., Alsalman, A.: A novel hybrid approach for a content-based image retrieval using feature fusion. Applied Sciences (2023). https:\/\/doi.org\/10.3390\/app13074581","journal-title":"Applied Sciences"},{"key":"6086_CR13","doi-asserted-by":"publisher","first-page":"103396","DOI":"10.1016\/j.jvcir.2021.103396","volume":"83","author":"J Pradhan","year":"2022","unstructured":"Pradhan, J., Pal, A.K., Banka, H.: A cbir system based on saliency driven local image features and multi orientation texture features. J. Vis. Commun. Image Represent. 83, 103396 (2022). https:\/\/doi.org\/10.1016\/j.jvcir.2021.103396. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1047320321002649)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"6086_CR14","doi-asserted-by":"publisher","first-page":"4187","DOI":"10.1007\/s10586-018-1731-0","volume":"22","author":"RR Saritha","year":"2018","unstructured":"Saritha, R.R., Paul, V., Kumar, P.G.: Content based image retrieval using deep learning process. Clust. Comput. 22, 4187\u20134200 (2018). (https:\/\/api.semanticscholar.org\/CorpusID:3309872)","journal-title":"Clust. Comput."},{"key":"6086_CR15","doi-asserted-by":"publisher","first-page":"1615","DOI":"10.1007\/s10462-019-09715-6","volume":"53","author":"SDMKKS Arun","year":"2020","unstructured":"Arun, S.D.M.K.K.S., Govindan, V.K.: Enhanced bag of visual words representations for content based image retrieval: a comparative study. Artif. Intell. Rev. 53, 1615\u20131653 (2020)","journal-title":"Artif. Intell. Rev."},{"key":"6086_CR16","doi-asserted-by":"publisher","first-page":"107952","DOI":"10.1016\/j.patcog.2021.107952","volume":"116","author":"QW Jian Zhang","year":"2021","unstructured":"Jian Zhang, Q.W., Cao, Y.: Vector of locally and adaptively aggregated descriptors for image feature representation. Pattern Recogn. 116, 107952 (2021). https:\/\/doi.org\/10.1016\/j.patcog.2021.107952. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0031320321001394)","journal-title":"Pattern Recogn."},{"issue":"1","key":"6086_CR17","doi-asserted-by":"publisher","first-page":"1927469","DOI":"10.1080\/23311916.2021.1927469","volume":"8","author":"SHA Ibtihaal","year":"2021","unstructured":"Ibtihaal, S.H.A., Hameed, M., Mahmmod, B.M.: Content-based image retrieval: a review of recent trends. Cogent Eng. 8(1), 1927469 (2021). https:\/\/doi.org\/10.1080\/23311916.2021.1927469","journal-title":"Cogent Eng."},{"key":"6086_CR18","doi-asserted-by":"publisher","first-page":"2226","DOI":"10.1109\/TMM.2022.3144890","volume":"25","author":"N Jiang","year":"2023","unstructured":"Jiang, N., Sheng, B., Li, P., Lee, T.-Y.: Photohelper: portrait photographing guidance via deep feature retrieval and fusion. IEEE Trans. Multimedia 25, 2226\u20132238 (2023). https:\/\/doi.org\/10.1109\/TMM.2022.3144890","journal-title":"IEEE Trans. Multimedia"},{"issue":"3","key":"6086_CR19","doi-asserted-by":"publisher","first-page":"2186","DOI":"10.1109\/TPAMI.2024.3519112","volume":"47","author":"Z Guan","year":"2025","unstructured":"Guan, Z., Zhao, W., Liu, H., Nakashima, Y., Babaguchi, N., He, X.: Cross-modal guided visual representation learning for social image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 47(3), 2186\u20132198 (2025). https:\/\/doi.org\/10.1109\/TPAMI.2024.3519112","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"6086_CR20","doi-asserted-by":"publisher","first-page":"27462","DOI":"10.1109\/ACCESS.2025.3538325","volume":"13","author":"Z Ur Rahman","year":"2025","unstructured":"Ur Rahman, Z., Lee, J.-H., Thanh Vu, D., Murtza, I., Kim, J.-Y.: Duco-net: dual-contrastive learning network for medical report retrieval leveraging enhanced encoders and augmentations. IEEE Access 13, 27462\u201327476 (2025). https:\/\/doi.org\/10.1109\/ACCESS.2025.3538325","journal-title":"IEEE Access"},{"key":"6086_CR21","unstructured":"Alappat, A.\u00a0L., Nakhate, P., Suman, S., Chandurkar, A., Pimpalkhute, V., Jain, T.: Cbir using pre-trained neural networks (2021). arXiv:2110.14455"},{"key":"6086_CR22","doi-asserted-by":"crossref","unstructured":"Russakovsky, O., Deng, J., Su, H.,\u00a0Krause, J., Satheesh, S.,\u00a0Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.\u00a0C., Fei-Fei, L.: Imagenet large scale visual recognition challenge (2014). arXiv:1409.0575","DOI":"10.1007\/s11263-015-0816-y"},{"key":"6086_CR23","doi-asserted-by":"publisher","unstructured":"Mohammed, M.\u00a0A., Oraibi, Z.\u00a0A., Hussain, M.\u00a0A.: Content based image retrieval using fine-tuned deep features with transfer learning, in: 2023 2nd International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE), pp. 108\u2013113 (2023). https:\/\/doi.org\/10.1109\/COSITE60233.2023.10249430","DOI":"10.1109\/COSITE60233.2023.10249430"},{"key":"6086_CR24","unstructured":"Anirudh, K., Siddha, G., Mehere, K.: Practical Deep Learning for Cloud, Mobile, and Edge, O\u2019Reilly Media, Inc., (2019)"},{"key":"6086_CR25","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1007\/978-3-319-10584-0_26","volume-title":"Computer Vision - ECCV 2014","author":"Y Gong","year":"2014","unstructured":"Gong, Y., Wang, L., Guo, R., Lazebnik, S.: Multi-scale orderless pooling of deep convolutional activation features. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) Computer Vision - ECCV 2014, pp. 392\u2013407. Springer International Publishing, Cham (2014)"},{"key":"6086_CR26","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR (2014). arXiv:1409.1556, https:\/\/api.semanticscholar.org\/CorpusID:14124313"},{"key":"6086_CR27","doi-asserted-by":"crossref","unstructured":"Li, Y., Kong, X., Zheng, L., Tian, Q.: Exploiting hierarchical activations of neural network for image retrieval, Proceedings of the 24th ACM international conference on Multimedia (2016). https:\/\/api.semanticscholar.org\/CorpusID:344190","DOI":"10.1145\/2964284.2967197"},{"key":"6086_CR28","doi-asserted-by":"publisher","unstructured":"Bhandi, V., Sumithra\u00a0Devi, K.\u00a0A.: Image retrieval by fusion of features from pre-trained deep convolution neural networks, in: 2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE), pp. 35\u201340 (2019). https:\/\/doi.org\/10.1109\/ICATIECE45860.2019.9063814","DOI":"10.1109\/ICATIECE45860.2019.9063814"},{"key":"6086_CR29","doi-asserted-by":"publisher","DOI":"10.1007\/s13735-018-0163-1","author":"H Li","year":"2019","unstructured":"Li, H., Ellis, J., Zhang, L., Chang, S.: Automatic visual pattern mining from categorical image dataset. International Journal of Multimedia Information Retrieval (2019). https:\/\/doi.org\/10.1007\/s13735-018-0163-1","journal-title":"International Journal of Multimedia Information Retrieval"},{"key":"6086_CR30","doi-asserted-by":"publisher","first-page":"57796","DOI":"10.1109\/ACCESS.2020.2982560","volume":"8","author":"X Li","year":"2020","unstructured":"Li, X., Yang, J., Ma, J.: Large scale category-structured image retrieval for object identification through supervised learning of cnn and surf-based matching. IEEE Access 8, 57796\u201357809 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2982560","journal-title":"IEEE Access"},{"key":"6086_CR31","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-06087-3","author":"A Ouni","year":"2021","unstructured":"Ouni, A., Royer, E., Chevaldonn\u00e9, M., Dhome, M.: Leveraging semantic segmentation for hybrid image retrieval methods. Neural Computing and Applications (2021). https:\/\/doi.org\/10.1007\/s00521-021-06087-3","journal-title":"Neural Computing and Applications"},{"key":"6086_CR32","doi-asserted-by":"publisher","unstructured":"Janjua, J., Patankar, A., Talan, A.: Exploring pretrained models and transfer learning techniques for image retrieval, in: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), pp. 1\u20137 (2023). https:\/\/doi.org\/10.1109\/ICCCNT56998.2023.10307272","DOI":"10.1109\/ICCCNT56998.2023.10307272"},{"key":"6086_CR33","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Commun. ACM 60, 84\u201390 (2012). (https:\/\/api.semanticscholar.org\/CorpusID:195908774)","journal-title":"Commun. ACM"},{"key":"6086_CR34","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition, in. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"6086_CR35","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S.E., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: Going deeper with convolutions. CoRR (2014). arXiv:1409.4842","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"6086_CR36","doi-asserted-by":"publisher","first-page":"120774","DOI":"10.1016\/j.eswa.2023.120774","volume":"232","author":"GS Vieira","year":"2023","unstructured":"Vieira, G.S., Fonseca, A.U., Sousa, N.M., Felix, J.P., Soares, F.: A novel content-based image retrieval system with feature descriptor integration and accuracy noise reduction. Expert Syst. Appl. 232, 120774 (2023). https:\/\/doi.org\/10.1016\/j.eswa.2023.120774. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417423012769)","journal-title":"Expert Syst. Appl."},{"key":"6086_CR37","unstructured":"Tan, M., Le, Q.\u00a0V.: Efficientnet: rethinking model scaling for convolutional neural networks, CoRR (2019). arXiv:1905.11946"},{"key":"6086_CR38","doi-asserted-by":"crossref","unstructured":"Ma, Chen, L.-C.: Mobilenetv2: inverted residuals and linear bottlenecks, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4510\u20134520 (2018)","DOI":"10.1109\/CVPR.2018.00474"},{"key":"6086_CR39","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1007\/s10791-007-9039-3","volume":"11","author":"T Deselaers","year":"2008","unstructured":"Deselaers, T., Keysers, D., Ney, H.: Features for image retrieval: an experimental comparison. Inf. Retr. 11, 77\u2013107 (2008). https:\/\/doi.org\/10.1007\/s10791-007-9039-3","journal-title":"Inf. Retr."},{"key":"6086_CR40","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.neucom.2014.03.014","volume":"141","author":"L Zhuo","year":"2014","unstructured":"Zhuo, L., Cheng, B., Zhang, J.: A comparative study of dimensionality reduction methods for large-scale image retrieval. Neurocomputing 141, 202\u2013210 (2014). https:\/\/doi.org\/10.1016\/j.neucom.2014.03.014. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0925231214004238)","journal-title":"Neurocomputing"},{"key":"6086_CR41","doi-asserted-by":"publisher","first-page":"10570","DOI":"10.1016\/j.eswa.2009.02.065","volume":"36","author":"NE Garc\u00eda-Pedrajas","year":"2009","unstructured":"Garc\u00eda-Pedrajas, N.E., Ortiz-Boyer, D.: Boosting k-nearest neighbor classifier by means of input space projection. Expert Syst. Appl. 36, 10570\u201310582 (2009). (https:\/\/api.semanticscholar.org\/CorpusID:32190966)","journal-title":"Expert Syst. Appl."},{"key":"6086_CR42","doi-asserted-by":"publisher","unstructured":"Michie, D., Spiegelhalter, D., Taylor, C.: Machine learning, neural and statistical classification. Technometrics 37 (1999). https:\/\/doi.org\/10.2307\/1269742","DOI":"10.2307\/1269742"},{"key":"6086_CR43","unstructured":"Satish\u00a0Tunga, D.\u00a0J., Gururaj, C.: A comparative study of content based image retrieval trends and approaches, International Journal of Image Processing (2015). https:\/\/api.semanticscholar.org\/CorpusID:165158911"},{"key":"6086_CR44","doi-asserted-by":"publisher","first-page":"550","DOI":"10.35940\/ijitee.B7711.029420","volume":"9","author":"S Ramakishore","year":"2020","unstructured":"Ramakishore, S., Karpagavalli, D.: K-nearest neighbor based enhanced-cbir system. Int. J. Innov. Technol. Explor. Eng. 9, 550\u2013554 (2020). https:\/\/doi.org\/10.35940\/ijitee.B7711.029420","journal-title":"Int. J. Innov. Technol. Explor. Eng."},{"key":"6086_CR45","doi-asserted-by":"publisher","unstructured":"Irawan, C., Listyaningsih, W., Setiadi, D.R.I.M, Sari, C.A, Rachmawanto, E.H.: Cbir for herbs root using color histogram and glcm based on k-nearest neighbor, in: 2018 International Seminar on Application for Technology of Information and Communication, pp. 509\u2013514. (2018)https:\/\/doi.org\/10.1109\/ISEMANTIC.2018.8549779","DOI":"10.1109\/ISEMANTIC.2018.8549779"},{"key":"6086_CR46","doi-asserted-by":"publisher","unstructured":"Alqasemi, F.A., Alabbasi, H.Q., Sabeha, F.G., Alawadhi, A., Kahlid, S., Zahary, A.: Feature selection approach using knn supervised learning for content-based image retrieval, in. First International Conference of Intelligent Computing and Engineering (ICOICE), pp. 1\u20135 (2019). https:\/\/doi.org\/10.1109\/ICOICE48418.2019.9035143","DOI":"10.1109\/ICOICE48418.2019.9035143"},{"key":"6086_CR47","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"6086_CR48","unstructured":"Yuvaraaj, M.: Exploring knn algorithm(brute force), accessed: 23-04-2024 (2020). https:\/\/medium.com\/@m.yuvarajmp\/exploring-knn-algorithm-brute-force-783656adef57\/"},{"key":"6086_CR49","unstructured":"Mattaparthi, G.: Ball tree and kd tree algorithms, accessed: 23-04-2024 (2024). https:\/\/medium.com\/@geethasreemattaparthi\/ball-tree-and-kd-tree-algorithms-a03cdc9f0af9"},{"key":"6086_CR50","unstructured":"Tyagi, V.: Content-Based Image Retrieval: Ideas, Influences, and Current Trends, 1st edn. Springer Publishing Company, Incorporated (2018a)"},{"key":"6086_CR51","doi-asserted-by":"publisher","first-page":"1854","DOI":"10.11591\/ijai.v12.i4.pp1854-1863","volume":"12","author":"R Hassan","year":"2023","unstructured":"Hassan, R., Sultani, Z., Dhannoon, B.: Content-based image retrieval based on corel dataset using deep learning. IAES International Journal of Artificial Intelligence (IJ-AI) 12, 1854 (2023). https:\/\/doi.org\/10.11591\/ijai.v12.i4.pp1854-1863","journal-title":"IAES International Journal of Artificial Intelligence (IJ-AI)"},{"key":"6086_CR52","unstructured":"Tyagi, V.: Similarity Measures and Performance Evaluation, 1st edn. Springer Publishing Company, Incorporated (2018b)"},{"issue":"1","key":"6086_CR53","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.cviu.2005.09.012","volume":"106","author":"L Fei-Fei","year":"2007","unstructured":"Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. Computer Vision and Image Understanding 106(1), 59\u201370 (2007)","journal-title":"Computer Vision and Image Understanding"},{"key":"6086_CR54","doi-asserted-by":"publisher","unstructured":"Ortega-Binderberger, M.: Corel Image Features, UCI Machine Learning Repository, https:\/\/doi.org\/10.24432\/C5K599 (1999)","DOI":"10.24432\/C5K599"},{"key":"6086_CR55","unstructured":"Nene, S.\u00a0A., Nayar, S.\u00a0K.,\u00a0Murase, H., et\u00a0al.: Columbia object image library (coil-20) (1996)"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-026-06086-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-026-06086-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-026-06086-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T18:07:11Z","timestamp":1784830031000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-026-06086-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":55,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["6086"],"URL":"https:\/\/doi.org\/10.1007\/s10586-026-06086-w","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"25 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 October 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 June 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"275"}}