{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T03:23:43Z","timestamp":1762658623565,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031299698"},{"type":"electronic","value":"9783031299704"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-29970-4_2","type":"book-chapter","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T14:06:26Z","timestamp":1682517986000},"page":"15-27","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Deep Recurrent Neural Network Performing Spectral Recurrence on\u00a0Hyperspectral Images for\u00a0Brain Tissue Classification"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9395-5807","authenticated-orcid":false,"given":"Pedro L.","family":"Cebri\u00e1n","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4715-6814","authenticated-orcid":false,"given":"Alberto","family":"Mart\u00edn-P\u00e9rez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7000-6289","authenticated-orcid":false,"given":"Manuel","family":"Villa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8767-6596","authenticated-orcid":false,"given":"Jaime","family":"Sancho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3236-1236","authenticated-orcid":false,"given":"Gonzalo","family":"Rosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5821-0877","authenticated-orcid":false,"given":"Guillermo","family":"Vazquez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5731-5199","authenticated-orcid":false,"given":"Pallab","family":"Sutradhar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2668-2903","authenticated-orcid":false,"given":"Alejandro","family":"Martinez de Ternero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0280-3440","authenticated-orcid":false,"given":"Miguel","family":"Chavarr\u00edas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3996-0554","authenticated-orcid":false,"given":"Alfonso","family":"Lagares","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6096-1511","authenticated-orcid":false,"given":"Eduardo","family":"Juarez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2411-9132","authenticated-orcid":false,"given":"C\u00e9sar","family":"Sanz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,4,27]]},"reference":[{"key":"2_CR1","doi-asserted-by":"publisher","unstructured":"Kraus, G.E., et al.: A technique utilizing positron emission tomography and magnetic resonance\/computed tomography image fusion to aid in surgical navigation and tumor volume determination. J. Image Guid. Surg., vol. 1, pp. 300\u2013307 (1995). https:\/\/doi.org\/10.1002\/(SICI)1522-712X(1995)1:6<300::AID-IGS2>3.0.CO;2-E","DOI":"10.1002\/(SICI)1522-712X(1995)1:6<300::AID-IGS2>3.0.CO;2-E"},{"key":"2_CR2","doi-asserted-by":"publisher","unstructured":"ElMasry, G., Sun, D.W.: Principles of hyperspectral imaging technology. In: Hyperspectral Imaging for Food Quality Analysis and Control. Academic Press, p. 3\u201343 (2010). https:\/\/doi.org\/10.1016\/B978-0-12-374753-2.10001-2","DOI":"10.1016\/B978-0-12-374753-2.10001-2"},{"issue":"11","key":"2_CR3","doi-asserted-by":"publisher","first-page":"3827","DOI":"10.3390\/s21113827","volume":"21","author":"G Urbanos","year":"2021","unstructured":"Urbanos, G., et al.: Supervised machine learning methods and hyperspectral imaging techniques jointly applied for brain cancer classification. Sensors 21(11), 3827 (2021). https:\/\/doi.org\/10.3390\/s21113827","journal-title":"Sensors"},{"key":"2_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1007\/978-3-030-11723-8_21","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"Y Zhou","year":"2019","unstructured":"Zhou, Y., et al.: Holistic brain tumor screening and classification based on DenseNet and recurrent neural network. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds.) BrainLes 2018. LNCS, vol. 11383, pp. 208\u2013217. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11723-8_21"},{"key":"2_CR5","doi-asserted-by":"publisher","unstructured":"Mou, L., Ghamisi, P., Zhu, X.X.: deep recurrent neural networks for hyperspectral image classification. IEEE Trans. Geosci. Remote Sens. 55(7), 3639\u20133655 . https:\/\/doi.org\/10.1109\/TGRS.2016.2636241","DOI":"10.1109\/TGRS.2016.2636241"},{"key":"2_CR6","doi-asserted-by":"publisher","unstructured":"Mart\u00edn-P\u00e9rez, A., et al.: Hyperparameter optimization for brain tumor classification with hyperspectral images. In: 2022 25th Euromicro Conference on Digital System Design (DSD) (2022). https:\/\/doi.org\/10.1109\/DSD57027.2022.00117","DOI":"10.1109\/DSD57027.2022.00117"},{"key":"2_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1007\/978-3-030-59716-0_66","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"M Bengs","year":"2020","unstructured":"Bengs, M., et al.: Spectral-spatial recurrent-convolutional networks for In-Vivo hyperspectral tumor type classification. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12263, pp. 690\u2013699. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59716-0_66"},{"key":"2_CR8","doi-asserted-by":"publisher","first-page":"7783","DOI":"10.3390\/app10217783","volume":"10","author":"H Ayaz","year":"2020","unstructured":"Ayaz, H., et al.: Hyperspectral imaging for minced meat classification using nonlinear deep features. Appl. Sci. 10, 7783 (2020). https:\/\/doi.org\/10.3390\/app10217783","journal-title":"Appl. Sci."},{"key":"2_CR9","doi-asserted-by":"publisher","first-page":"507","DOI":"10.3390\/diagnostics12020507","volume":"12","author":"L Knospe","year":"2022","unstructured":"Knospe, L., et al.: New intraoperative imaging tools and image-guided surgery in gastric cancer surgery. Diagnostics 12, 507 (2022). https:\/\/doi.org\/10.3390\/diagnostics12020507","journal-title":"Diagnostics"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Wang, L.: Support Vector Machines: Theory and Applications. Springer Science & Business Media, Auckland, vol. 177 (2005)","DOI":"10.1007\/b95439"},{"key":"2_CR11","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001). https:\/\/doi.org\/10.1023\/A:1010933404324","journal-title":"Mach. Learn."},{"issue":"1","key":"2_CR12","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/S0169-7439(97)00061-0","volume":"39","author":"D Svozil","year":"1997","unstructured":"Svozil, D., Kvasnicka, V., Pospichal, J.: Introduction to multi-layer feed-forward neural networks. Chemometri. Intell. Lab. Syst. 39(1), 43\u201362 (1997). https:\/\/doi.org\/10.1016\/S0169-7439(97)00061-0","journal-title":"Chemometri. Intell. Lab. Syst."},{"key":"2_CR13","doi-asserted-by":"publisher","unstructured":"Pascanu, R., et al.: On the difficulty of training recurrent neural networks. Proceedings of the 30th International Conference on Machine Learning, in Proceedings of Machine Learning Research, vol. 28, no. 3, pp. 1310\u20131318 (2013). https:\/\/doi.org\/10.48550\/arXiv.1211.5063. https:\/\/proceedings.mlr.press\/v28\/pascanu13.html","DOI":"10.48550\/arXiv.1211.5063"},{"key":"2_CR14","unstructured":"Bergstra, J., et al.: Algorithms for hyperparameter optimization. In: Advances in Neural Information Processing Systems, vol. 24 (2011). https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2011\/file\/86e8f7ab32cfd12577bc2619bc635690-Paper.pdf"},{"key":"2_CR15","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1016\/j.isprsjprs.2018.05.014","volume":"142","author":"Y Xu","year":"2018","unstructured":"Xu, Y., et al.: Hyperspectral image classification via a random patches network. ISPRS J. Photogrammetry Remote Sens. 142, 344\u2013357 (2018). https:\/\/doi.org\/10.1016\/j.isprsjprs.2018.05.014","journal-title":"ISPRS J. Photogrammetry Remote Sens."}],"container-title":["Lecture Notes in Computer Science","Design and Architecture for Signal and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-29970-4_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T14:06:36Z","timestamp":1682517996000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-29970-4_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031299698","9783031299704"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-29970-4_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"27 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Design and Architecture for Signal and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toulouse","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 January 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 January 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasip2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/dasip23.citsem.upm.es\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17","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":"9","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":"53% - 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":"1.4","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}