{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T18:06:25Z","timestamp":1743098785223,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030878962"},{"type":"electronic","value":"9783030878979"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-87897-9_2","type":"book-chapter","created":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T17:23:18Z","timestamp":1633454598000},"page":"15-24","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Contextual Image Classification Through Fine-Tuned Graph Neural Networks"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2890-1436","authenticated-orcid":false,"given":"Walacy S.","family":"Campos","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7380-0944","authenticated-orcid":false,"given":"Luis G.","family":"Souza","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4870-4766","authenticated-orcid":false,"given":"Priscila T. M.","family":"Saito","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9421-9254","authenticated-orcid":false,"given":"Pedro H.","family":"Bugatti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,6]]},"reference":[{"key":"2_CR1","doi-asserted-by":"publisher","unstructured":"Andonie, R.: Hyperparameter optimization in learning systems. J. Membr. Comput. 1\u201313 (2019). https:\/\/doi.org\/10.1007\/s41965-019-00023-0","DOI":"10.1007\/s41965-019-00023-0"},{"issue":"4","key":"2_CR2","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MSP.2017.2693418","volume":"34","author":"MM Bronstein","year":"2017","unstructured":"Bronstein, M.M., Bruna, J., Lecun, Y., Szlam, A., Vandergheynst, P.: Geometric deep learning: going beyond euclidean data. IEEE Sig. Process. Mag. 34(4), 18\u201342 (2017)","journal-title":"IEEE Sig. Process. Mag."},{"key":"2_CR3","unstructured":"Bruna, J., Zaremba, W., Szlam, A., LeCun, Y.: Spectral networks and deep locally connected networks on graphs. In: Proceedings of the International Conference on Learning Representations, pp. 1\u201314 (2014)"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Chen, X., Gupta, A.: Spatial memory for context reasoning in object detection. CoRR abs\/1704.04224 (2017)","DOI":"10.1109\/ICCV.2017.440"},{"key":"2_CR5","doi-asserted-by":"crossref","unstructured":"Chen, X., Li, L., Fei-Fei, L., Gupta, A.: Iterative visual reasoning beyond convolutions. CoRR abs\/1803.11189 (2018)","DOI":"10.1109\/CVPR.2018.00756"},{"key":"2_CR6","doi-asserted-by":"crossref","unstructured":"Chung, H., Huang, H., Chen, H.: Predicting future participants of information propagation trees. In: Proceedings of the IEEE\/WIC\/ACM International Conference on Web Intelligence, pp. 321\u2013325 (2019)","DOI":"10.1145\/3350546.3352540"},{"key":"2_CR7","doi-asserted-by":"crossref","unstructured":"Gallicchio, C., Micheli, A.: Graph echo state networks. In: Proceedings of the International Joint Conference on Neural Networks, pp. 1\u20138 (2010)","DOI":"10.1109\/IJCNN.2010.5596796"},{"key":"2_CR8","doi-asserted-by":"crossref","unstructured":"Gori, M., Monfardini, G., Scarselli, F.: A new model for learning in graph domains. In: Proceedings of the IEEE International Joint Conference on Neural Networks, vol. 2, pp. 729\u2013734 (2005)","DOI":"10.1109\/IJCNN.2005.1555942"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR abs\/1512.03385 (2015)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"9","key":"2_CR10","doi-asserted-by":"publisher","first-page":"2507","DOI":"10.1109\/TKDE.2015.2391125","volume":"27","author":"L Hong","year":"2015","unstructured":"Hong, L., Zou, L., Lian, X., Yu, P.S.: Subgraph matching with set similarity in a large graph database. IEEE Trans. Knowl. Data Eng. 27(9), 2507\u20132521 (2015)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"2_CR11","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"2_CR12","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. In: Proceedings of the International Conference on Learning Representations, pp. 1\u201314 (2019)"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Li, Q., Han, Z., Wu, X.: Deeper insights into graph convolutional networks for semi-supervised learning. CoRR abs\/1801.07606 (2018)","DOI":"10.1609\/aaai.v32i1.11604"},{"key":"2_CR14","doi-asserted-by":"crossref","unstructured":"Marino, K., Salakhutdinov, R., Gupta, A.: The more you know: Using knowledge graphs for image classification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 20\u201328 (2017)","DOI":"10.1109\/CVPR.2017.10"},{"key":"2_CR15","doi-asserted-by":"crossref","unstructured":"Quattoni, A., Torralba, A.: Recognizing indoor scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 413\u2013420 (2009)","DOI":"10.1109\/CVPRW.2009.5206537"},{"issue":"1","key":"2_CR16","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TNN.2008.2005605","volume":"20","author":"F Scarselli","year":"2009","unstructured":"Scarselli, F., Gori, M., Tsoi, A.C., Hagenbuchner, M., Monfardini, G.: The graph neural network model. IEEE Trans. Neural Netw. 20(1), 61\u201380 (2009)","journal-title":"IEEE Trans. Neural Netw."},{"key":"2_CR17","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556 (2014)"},{"issue":"3","key":"2_CR18","doi-asserted-by":"publisher","first-page":"714","DOI":"10.1109\/72.572108","volume":"8","author":"A Sperduti","year":"1997","unstructured":"Sperduti, A., Starita, A.: Supervised neural networks for the classification of structures. IEEE Trans. Neural Netw. 8(3), 714\u2013735 (1997)","journal-title":"IEEE Trans. Neural Netw."},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. CoRR abs\/1512.00567 (2015)","DOI":"10.1109\/CVPR.2016.308"},{"key":"2_CR20","unstructured":"Tan, M., Le, Q.V.: Efficientnet: rethinking model scaling for convolutional neural networks. CoRR abs\/1905.11946 (2019)"},{"key":"2_CR21","unstructured":"Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., Yu, P.S.: A comprehensive survey on graph neural networks. CoRR abs\/1901.00596 (2019)"},{"key":"2_CR22","unstructured":"Zhou, J., Cui, G., Zhang, Z., Yang, C., Liu, Z., Sun, M.: Graph neural networks: a review of methods and applications. CoRR abs\/1812.08434 (2018)"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence and Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-87897-9_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T10:09:21Z","timestamp":1725876561000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-87897-9_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030878962","9783030878979"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-87897-9_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"6 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICAISC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence and Soft Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 June 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 June 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icaisc2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/icaisc2021.icaisc.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Own Online System","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"195","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"89","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"46% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}