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Imaging"],"abstract":"<jats:p>This paper describes in detail VISIONE, a video search system that allows users to search for videos using textual keywords, the occurrence of objects and their spatial relationships, the occurrence of colors and their spatial relationships, and image similarity. These modalities can be combined together to express complex queries and meet users\u2019 needs. The peculiarity of our approach is that we encode all information extracted from the keyframes, such as visual deep features, tags, color and object locations, using a convenient textual encoding that is indexed in a single text retrieval engine. This offers great flexibility when results corresponding to various parts of the query (visual, text and locations) need to be merged. In addition, we report an extensive analysis of the retrieval performance of the system, using the query logs generated during the Video Browser Showdown (VBS) 2019 competition. This allowed us to fine-tune the system by choosing the optimal parameters and strategies from those we tested.<\/jats:p>","DOI":"10.3390\/jimaging7050076","type":"journal-article","created":{"date-parts":[[2021,4,23]],"date-time":"2021-04-23T12:08:30Z","timestamp":1619179710000},"page":"76","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["The VISIONE Video Search System: Exploiting Off-the-Shelf Text Search Engines for Large-Scale Video Retrieval"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0171-4315","authenticated-orcid":false,"given":"Giuseppe","family":"Amato","sequence":"first","affiliation":[{"name":"Institute of Information Science and Technologies (ISTI), Italian National Research Council (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5225-4278","authenticated-orcid":false,"given":"Paolo","family":"Bolettieri","sequence":"additional","affiliation":[{"name":"Institute of Information Science and Technologies (ISTI), Italian National Research Council (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5014-5089","authenticated-orcid":false,"given":"Fabio","family":"Carrara","sequence":"additional","affiliation":[{"name":"Institute of Information Science and Technologies (ISTI), Italian National Research Council (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0369-6045","authenticated-orcid":false,"given":"Franca","family":"Debole","sequence":"additional","affiliation":[{"name":"Institute of Information Science and Technologies (ISTI), Italian National Research Council (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6258-5313","authenticated-orcid":false,"given":"Fabrizio","family":"Falchi","sequence":"additional","affiliation":[{"name":"Institute of Information Science and Technologies (ISTI), Italian National Research Council (CNR), Via G. 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Multimed."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"5539","DOI":"10.1007\/s11042-016-3661-2","article-title":"Interactive video search tools: A detailed analysis of the video browser showdown 2015","volume":"76","author":"Schoeffmann","year":"2017","journal-title":"Multimed. Tools Appl."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3361","DOI":"10.1109\/TMM.2018.2830110","article-title":"On influential trends in interactive video retrieval: Video Browser Showdown 2015\u20132017","volume":"20","author":"Bailer","year":"2018","journal-title":"IEEE Trans. Multimed."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Berns, F., Rossetto, L., Schoeffmann, K., Beecks, C., and Awad, G. (2019, January 10\u201313). V3C1 Dataset: An Evaluation of Content Characteristics. Proceedings of the 2019 on International Conference on Multimedia Retrieval, Ottawa, ON, Canada.","DOI":"10.1145\/3323873.3325051"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Amato, G., Bolettieri, P., Carrara, F., Debole, F., Falchi, F., Gennaro, C., Vadicamo, L., and Vairo, C. (2019). VISIONE at VBS2019. Lecture Notes in Computer Science, Proceedings of the MultiMedia Modeling, Thessaloniki, Greece, 8\u201311 January 2019, Springer International Publishing.","DOI":"10.1007\/978-3-030-05716-9_51"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hu, P., Zhen, L., Peng, D., and Liu, P. (2019, January 21\u201325). Scalable deep multimodal learning for cross-modal retrieval. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Paris, France.","DOI":"10.1145\/3331184.3331213"},{"key":"ref_7","unstructured":"Liu, Y., Albanie, S., Nagrani, A., and Zisserman, A. (2019). Use what you have: Video retrieval using representations from collaborative experts. arXiv."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Mithun, N.C., Li, J., Metze, F., and Roy-Chowdhury, A.K. (2018, January 11\u201314). Learning joint embedding with multimodal cues for cross-modal video-text retrieval. Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval, Yokohama, Japan.","DOI":"10.1145\/3206025.3206064"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Otani, M., Nakashima, Y., Rahtu, E., Heikkil\u00e4, J., and Yokoya, N. (2016). Learning joint representations of videos and sentences with web image search. European Conference on Computer Vision, Springer. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-319-46604-0_46"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zhen, L., Hu, P., Wang, X., and Peng, D. (2019, January 16\u201320). Deep supervised cross-modal retrieval. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.01064"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1006\/cviu.1999.0765","article-title":"Unifying textual and visual cues for content-based image retrieval on the world wide web","volume":"75","author":"Sclaroff","year":"1999","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_12","unstructured":"Frome, A., Corrado, G.S., Shlens, J., Bengio, S., Dean, J., Ranzato, M., and Mikolov, T. (2013, January 5\u201310). Devise: A deep visual-semantic embedding model. Proceedings of the Advances in Neural Information Processing Systems, Lake Tahoe, NV, USA."},{"key":"ref_13","unstructured":"Kiros, R., Salakhutdinov, R., and Zemel, R.S. (2014). Unifying visual-semantic embeddings with multimodal neural language models. arXiv."},{"key":"ref_14","unstructured":"Karpathy, A., Joulin, A., and Fei-Fei, L.F. (2014, January 8\u201313). Deep fragment embeddings for bidirectional image sentence mapping. Proceedings of the Advances in Neural Information Processing Systems, Montreal, QC, Canada."},{"key":"ref_15","unstructured":"Dong, J., Li, X., and Snoek, C.G. (2016). Word2visualvec: Image and video to sentence matching by visual feature prediction. arXiv."},{"key":"ref_16","unstructured":"Miech, A., Zhukov, D., Alayrac, J.B., Tapaswi, M., Laptev, I., and Sivic, J. (November, January 27). Howto100m: Learning a text-video embedding by watching hundred million narrated video clips. Proceedings of the IEEE International Conference on Computer Vision, Seoul, Korea."},{"key":"ref_17","unstructured":"Pan, Y., Mei, T., Yao, T., Li, H., and Rui, Y. (July, January 26). Jointly modeling embedding and translation to bridge video and language. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Xu, R., Xiong, C., Chen, W., and Corso, J.J. (2015, January 25\u201330). Jointly Modeling Deep Video and Compositional Text to Bridge Vision and Language in a Unified Framework. Proceedings of the AAAI Conference on Artificial Intelligence, Austin, TX, USA.","DOI":"10.1609\/aaai.v29i1.9512"},{"key":"ref_19","unstructured":"La Cascia, M., and Ardizzone, E. (1996, January 9). Jacob: Just a content-based query system for video databases. Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, Atlanta, GA, USA."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Marques, O., and Furht, B. (2002). Content-Based Image and Video Retrieval, Springer Science & Business Media.","DOI":"10.1007\/978-1-4615-0987-5"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Patel, B., and Meshram, B. (2012). Content based video retrieval systems. arXiv.","DOI":"10.5121\/iju.2012.3202"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/BF00962238","article-title":"Efficient and effective querying by image content","volume":"3","author":"Faloutsos","year":"1994","journal-title":"J. Intell. Inf. Syst."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Schoeffmann, K. (2019, January 4\u20136). Video Browser Showdown 2012\u20132019: A Review. Proceedings of the 2019 International Conference on Content-Based Multimedia Indexing (CBMI), Dublin, Ireland.","DOI":"10.1109\/CBMI.2019.8877397"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Loko\u010d, J., Koval\u010d\u00edk, G., M\u00fcnzer, B., Sch\u00f6ffmann, K., Bailer, W., Gasser, R., Vrochidis, S., Nguyen, P.A., Rujikietgumjorn, S., and Barthel, K.U. (2019). Interactive Search or Sequential Browsing? A Detailed Analysis of the Video Browser Showdown 2018. ACM Trans. Multimed. Comput. Commun. Appl., 15.","DOI":"10.1145\/3295663"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Loko\u010d, J., Koval\u010d\u00edk, G., and Sou\u010dek, T. (2018). Revisiting SIRET Video Retrieval Tool. International Conference on Multimedia Modeling, Springer. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-319-73600-6_44"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Rossetto, L., Amiri Parian, M., Gasser, R., Giangreco, I., Heller, S., and Schuldt, H. (2019). Deep Learning-Based Concept Detection in vitrivr. International Conference on Multimedia Modeling, Springer International Publishing. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-030-05716-9_55"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kratochv\u00edl, M., Vesel\u00fd, P., Mejzl\u00edk, F., and Loko\u010d, J. (2020). SOM-Hunter: Video Browsing with Relevance-to-SOM Feedback Loop. International Conference on Multimedia Modeling, Springer International Publishing. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-030-37734-2_71"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Loko\u010d, J., Koval\u010d\u00edk, G., and Sou\u010dek, T. (2020). VIRET at Video Browser Showdown 2020. International Conference on Multimedia Modeling, Springer International Publishing. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-030-37734-2_70"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zoph, B., Vasudevan, V., Shlens, J., and Le, Q.V. (2018, January 18\u201322). Learning transferable architectures for scalable image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Li, X., Xu, C., Yang, G., Chen, Z., and Dong, J. (2019, January 21\u201325). W2VV++ Fully Deep Learning for Ad-hoc Video Search. Proceedings of the 27th ACM International Conference on Multimedia, Nice, France.","DOI":"10.1145\/3343031.3350906"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Sauter, L., Amiri Parian, M., Gasser, R., Heller, S., Rossetto, L., and Schuldt, H. (2020). Combining Boolean and Multimedia Retrieval in vitrivr for Large-Scale Video Search. International Conference on Multimedia Modeling, Springer International Publishing. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-030-37734-2_66"},{"key":"ref_32","unstructured":"Rossetto, L., Gasser, R., and Schuldt, H. (2019). Query by Semantic Sketch. arXiv."},{"key":"ref_33","unstructured":"Ren, S., He, K., Girshick, R., and Sun, J. (2015, January 7\u201312). Faster R-CNN: Towards real-time object detection with region proposal networks. Proceedings of the Advances in Neural Information Processing Systems, Montreal, QC, Canada."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/TCSVT.2002.808079","article-title":"CBSA: Content-based soft annotation for multimodal image retrieval using Bayes point machines","volume":"13","author":"Chang","year":"2003","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1109\/TPAMI.2007.61","article-title":"Supervised Learning of Semantic Classes for Image Annotation and Retrieval","volume":"29","author":"Carneiro","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_36","unstructured":"Barnard, K., and Forsyth, D. (2001, January 7\u201314). Learning the semantics of words and pictures. Proceedings of the Eighth IEEE International Conference on Computer Vision, ICCV 2001, Vancouver, BC, Canada."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Li, X., Uricchio, T., Ballan, L., Bertini, M., Snoek, C.G.M., and Bimbo, A.D. (2016). Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement, and Retrieval. ACM Comput. Surv., 49.","DOI":"10.1145\/2906152"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"16389","DOI":"10.1007\/s11042-016-3918-9","article-title":"Local and global approaches for unsupervised image annotation","volume":"76","author":"Pellegrin","year":"2016","journal-title":"Multimed. Tools Appl."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Amato, G., Falchi, F., Gennaro, C., and Rabitti, F. (2017, January 19\u201321). Searching and annotating 100M Images with YFCC100M-HNfc6 and MI-File. Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing, Florence, Italy.","DOI":"10.1145\/3095713.3095740"},{"key":"ref_40","unstructured":"Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., and Darrell, T. (2013). DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. arXiv."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Babenko, A., Slesarev, A., Chigorin, A., and Lempitsky, V. (2014). Neural codes for image retrieval. European Conference on Computer Vision, Springer. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-319-10590-1_38"},{"key":"ref_42","unstructured":"Razavian, A.S., Sullivan, J., Carlsson, S., and Maki, A. (2014). Visual instance retrieval with deep convolutional networks. arXiv."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., and Malik, J. (2014, January 23\u201328). Rich feature hierarchies for accurate object detection and semantic segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Razavian, A.S., Azizpour, H., Sullivan, J., and Carlsson, S. (2014, January 23\u201328). CNN features off-the-shelf: An astounding baseline for recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, IEEE Computer Society, Columbus, OH, USA.","DOI":"10.1109\/CVPRW.2014.131"},{"key":"ref_45","unstructured":"Tolias, G., Sicre, R., and J\u00e9gou, H. (2015). Particular object retrieval with integral max-pooling of CNN activations. arXiv."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s11263-017-1016-8","article-title":"End-to-End Learning of Deep Visual Representations for Image Retrieval","volume":"124","author":"Gordo","year":"2017","journal-title":"Int. J. Comput. Vis."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.procs.2016.07.220","article-title":"SIFT and tensor based object detection and classification in videos using deep neural networks","volume":"93","author":"Najva","year":"2016","journal-title":"Procedia Comput. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1152","DOI":"10.1109\/TCC.2016.2517653","article-title":"Video stream analysis in clouds: An object detection and classification framework for high performance video analytics","volume":"7","author":"Anjum","year":"2016","journal-title":"IEEE Trans. Cloud Comput."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.future.2017.02.003","article-title":"Cloud-based scalable object detection and classification in video streams","volume":"80","author":"Yaseen","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"15751","DOI":"10.1007\/s11042-018-7031-0","article-title":"Object detection and classification: A joint selection and fusion strategy of deep convolutional neural network and SIFT point features","volume":"78","author":"Rashid","year":"2019","journal-title":"Multimed. Tools Appl."},{"key":"ref_51","unstructured":"Redmon, J., and Farhadi, A. (2018). YOLOv3: An Incremental Improvement. arXiv."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Redmon, J., and Farhadi, A. (2017, January 21\u201326). YOLO9000: Better, faster, stronger. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref_53","unstructured":"Redmon, J., and Farhadi, A. (2019, February 28). YOLOv3 on the Open Images Dataset. Available online: https:\/\/pjreddie.com\/darknet\/yolo\/."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Gennaro, C., Amato, G., Bolettieri, P., and Savino, P. (2010). An approach to content-based image retrieval based on the Lucene search engine library. International Conference on Theory and Practice of Digital Libraries, Springer. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-642-15464-5_8"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Amato, G., Bolettieri, P., Carrara, F., Falchi, F., and Gennaro, C. (2018, January 8\u201312). Large-Scale Image Retrieval with Elasticsearch. Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, Ann Arbor, MI, USA.","DOI":"10.1145\/3209978.3210089"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Amato, G., Carrara, F., Falchi, F., Gennaro, C., and Vadicamo, L. (2019). Large-scale instance-level image retrieval. Inf. Process. Manag., 102100.","DOI":"10.1016\/j.ipm.2019.102100"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Amato, G., Carrara, F., Falchi, F., and Gennaro, C. (2017, January 6\u20139). Efficient Indexing of Regional Maximum Activations of Convolutions using Full-Text Search Engines. Proceedings of the ACM International Conference on Multimedia Retrieval, ACM, Bucharest, Romania.","DOI":"10.1145\/3078971.3079035"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1145\/2812802","article-title":"YFCC100M: The New Data in Multimedia Research","volume":"59","author":"Thomee","year":"2016","journal-title":"Commun. ACM"},{"key":"ref_59","unstructured":"Miller, G. (1998). WordNet: An Electronic Lexical Database, MIT Press. Language, Speech, and Communication."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1333","DOI":"10.1007\/s11042-012-1271-1","article-title":"MI-File: Using inverted files for scalable approximate similarity search","volume":"71","author":"Amato","year":"2012","journal-title":"Multimed. Tools Appl."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Truong, T.D., Nguyen, V.T., Tran, M.T., Trieu, T.V., Do, T., Ngo, T.D., and Le, D.D. (2018). Video Search Based on Semantic Extraction and Locally Regional Object Proposal. International Conference on Multimedia Modeling, Springer. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-319-73600-6_49"},{"key":"ref_62","unstructured":"Rubner, Y., Guibas, L., and Tomasi, C. (1997, January 11\u201314). The Earth Mover\u2019s Distance, MultiDimensional Scaling, and Color-Based Image Retrieval. Proceedings of the ARPA Image Understanding Workshop, New Orleans, LA, USA."},{"key":"ref_63","unstructured":"Shang, W., Sohn, K., Almeida, D., and Lee, H. (2016, January 20\u201322). Understanding and improving convolutional neural networks via concatenated rectified linear units. Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA."},{"key":"ref_64","first-page":"109","article-title":"Okapi at TREC-3","volume":"Volume 500\u2013225","author":"Robertson","year":"1994","journal-title":"Proceedings of the Third Text REtrieval Conference, TREC 1994"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1108\/eb026526","article-title":"A statistical interpretation of term specificity and its application in retrieval","volume":"28","year":"1972","journal-title":"J. Doc."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Smucker, M.D., Allan, J., and Carterette, B. (2007, January 6\u20138). A Comparison of Statistical Significance Tests for Information Retrieval Evaluation. Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management, Lisboa, Portugal.","DOI":"10.1145\/1321440.1321528"}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/7\/5\/76\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:51:50Z","timestamp":1760161910000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/7\/5\/76"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,23]]},"references-count":66,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["jimaging7050076"],"URL":"https:\/\/doi.org\/10.3390\/jimaging7050076","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,23]]}}}