{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T07:39:19Z","timestamp":1743061159359,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031510250"},{"type":"electronic","value":"9783031510267"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-51026-7_37","type":"book-chapter","created":{"date-parts":[[2024,1,20]],"date-time":"2024-01-20T14:02:08Z","timestamp":1705759328000},"page":"437-448","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Convolutional Generative Model for\u00a0Pixel\u2013Wise Colour Specification for\u00a0Cultural Heritage"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8901-289X","authenticated-orcid":false,"given":"Furnari","family":"Giuseppe","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3339-7799","authenticated-orcid":false,"given":"Anna Maria","family":"Gueli","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3865-9911","authenticated-orcid":false,"given":"Stanco","family":"Filippo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4819-5340","authenticated-orcid":false,"given":"Dario","family":"Allegra","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,21]]},"reference":[{"key":"37_CR1","doi-asserted-by":"crossref","unstructured":"Allegra, D., et al.: A method to improve the color rendering accuracy in cultural heritage: preliminary results. In: Journal of Physics: Conference Series, vol. 2204, p. 012057. IOP Publishing (2022)","DOI":"10.1088\/1742-6596\/2204\/1\/012057"},{"key":"37_CR2","doi-asserted-by":"publisher","first-page":"1535","DOI":"10.1016\/j.procs.2020.04.164","volume":"171","author":"K Bajaj","year":"2020","unstructured":"Bajaj, K., Singh, D.K., Ansari, M.A.: Autoencoders based deep learner for image denoising. Procedia Comput. Sci. 171, 1535\u20131541 (2020)","journal-title":"Procedia Comput. Sci."},{"key":"37_CR3","unstructured":"Bank, D., Koenigstein, N., Giryes, R.: Autoencoders. arXiv preprint: arXiv:2003.05991 (2020)"},{"issue":"4","key":"37_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2601097.2601206","volume":"33","author":"S Bell","year":"2014","unstructured":"Bell, S., Bala, K., Snavely, N.: Intrinsic images in the wild. ACM Trans. Graph. (TOG) 33(4), 1\u201312 (2014)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"37_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Q., Koltun, V.: A simple model for intrinsic image decomposition with depth cues. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 241\u2013248 (2013)","DOI":"10.1109\/ICCV.2013.37"},{"key":"37_CR6","doi-asserted-by":"crossref","unstructured":"Chen, Y., Liu, D., Liang, J.: A new method for RGB to CIELAB color space transformation based on Markov chain monte Carlo. In: MIPPR 2013: Parallel Processing of Images and Optimization and Medical Imaging Processing, vol. 8920, pp. 102\u2013108. SPIE (2013)","DOI":"10.1117\/12.2031555"},{"key":"37_CR7","doi-asserted-by":"crossref","unstructured":"Chu, S.J., Trushkowsky, R.D., Paravina, R.D.: Dental color matching instruments and systems. Review of clinical and research aspects. J. Dentistry 38, e2\u2013e16 (2010)","DOI":"10.1016\/j.jdent.2010.07.001"},{"key":"37_CR8","doi-asserted-by":"crossref","unstructured":"Fan, Q., Yang, J., Hua, G., Chen, B., Wipf, D.: Revisiting deep intrinsic image decompositions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8944\u20138952 (2018)","DOI":"10.1109\/CVPR.2018.00932"},{"key":"37_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1007\/978-3-642-10467-1_97","volume-title":"Advances in Multimedia Information Processing - PCM 2009","author":"N Fdhal","year":"2009","unstructured":"Fdhal, N., Kyan, M., Androutsos, D., Sharma, A.: Color space transformation from RGB to CIELAB using neural networks. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds.) PCM 2009. LNCS, vol. 5879, pp. 1011\u20131017. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-10467-1_97"},{"issue":"2","key":"37_CR10","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.patcog.2004.04.010","volume":"38","author":"G Finlayson","year":"2005","unstructured":"Finlayson, G., Hordley, S., Schaefer, G., Tian, G.Y.: Illuminant and device invariant colour using histogram equalisation. Pattern Recogn. 38(2), 179\u2013190 (2005)","journal-title":"Pattern Recogn."},{"issue":"11","key":"37_CR11","doi-asserted-by":"publisher","first-page":"7624","DOI":"10.1109\/TPAMI.2021.3119551","volume":"44","author":"D Forsyth","year":"2021","unstructured":"Forsyth, D., Rock, J.J.: Intrinsic image decomposition using paradigms. IEEE Trans. Pattern Anal. Mach. Intell. 44(11), 7624\u20137637 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"37_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/978-3-031-37731-0_2","volume-title":"Pattern Recognition, Computer Vision, and Image Processing","author":"F Giuseppe","year":"2023","unstructured":"Giuseppe, F., Dario, A., Anna, G., Filippo, S.: CIELab color measurement through RGB-D images. In: Rousseau, J.J., Kapralos, B. (eds.) Pattern Recognition, Computer Vision, and Image Processing. Lecture Notes in Computer Science, vol. 13645, pp. 15\u201320. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-37731-0_2"},{"key":"37_CR13","unstructured":"Giuseppe, F., Gueli, A.M., Stanco, F., Allegra, D.: PixelwiseColourSpecification. https:\/\/github.com\/giuseppefrn\/PixelwiseColourSpecification\/"},{"key":"37_CR14","doi-asserted-by":"crossref","unstructured":"Gong, D., et al.: Memorizing normality to detect anomaly: memory-augmented deep autoencoder for unsupervised anomaly detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1705\u20131714 (2019)","DOI":"10.1109\/ICCV.2019.00179"},{"issue":"11","key":"37_CR15","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow, I., et al.: Generative adversarial networks. Commun. ACM 63(11), 139\u2013144 (2020)","journal-title":"Commun. ACM"},{"issue":"5","key":"37_CR16","doi-asserted-by":"publisher","first-page":"684","DOI":"10.1002\/col.22115","volume":"42","author":"AM Gueli","year":"2017","unstructured":"Gueli, A.M., Pedull\u00e0, E., Pasquale, S., La Rosa, G.R., Rapisarda, E.: Color specification of two new resin composites and influence of stratification on their chromatic perception. Color. Res. Appl. 42(5), 684\u2013692 (2017)","journal-title":"Color. Res. Appl."},{"key":"37_CR17","unstructured":"Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.C.: Improved training of Wasserstein GANs. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"37_CR18","doi-asserted-by":"crossref","unstructured":"Iturbe, A., Cachero, R., Canal, D., Martos, A.: Virtual digitization of caves with parietal paleolithic art from Bizkaia. Scientific analysis and dissemination through new visualization techniques. Virtual Archaeol. Rev. 9(18), 57\u201365 (2018)","DOI":"10.4995\/var.2018.7579"},{"issue":"6","key":"37_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2070781.2024191","volume":"30","author":"K Karsch","year":"2011","unstructured":"Karsch, K., Hedau, V., Forsyth, D., Hoiem, D.: Rendering synthetic objects into legacy photographs. ACM Trans. Graph. (TOG) 30(6), 1\u201312 (2011)","journal-title":"ACM Trans. Graph. (TOG)"},{"issue":"6","key":"37_CR20","doi-asserted-by":"publisher","first-page":"932","DOI":"10.1016\/j.eujim.2016.04.002","volume":"8","author":"T Kawanabe","year":"2016","unstructured":"Kawanabe, T., et al.: Quantification of tongue Colour using machine learning in Kampo medicine. Eur. J. Integr. Med. 8(6), 932\u2013941 (2016)","journal-title":"Eur. J. Integr. Med."},{"issue":"3","key":"37_CR21","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1002\/col.22092","volume":"42","author":"P Korytkowski","year":"2017","unstructured":"Korytkowski, P., Olejnik-Krugly, A.: Precise capture of colors in cultural heritage digitization. Color. Res. Appl. 42(3), 333\u2013336 (2017)","journal-title":"Color. Res. Appl."},{"key":"37_CR22","doi-asserted-by":"crossref","unstructured":"Kovacs, B., Bell, S., Snavely, N., Bala, K.: Shading annotations in the wild. Comput. Vis. Pattern Recogn. (CVPR) (2017)","DOI":"10.1109\/CVPR.2017.97"},{"issue":"5","key":"37_CR23","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1007\/s11747-010-0245-y","volume":"40","author":"LI Labrecque","year":"2012","unstructured":"Labrecque, L.I., Milne, G.R.: Exciting red and competent blue: the importance of color in marketing. J. Acad. Mark. Sci. 40(5), 711\u2013727 (2012)","journal-title":"J. Acad. Mark. Sci."},{"issue":"10","key":"37_CR24","doi-asserted-by":"publisher","first-page":"1084","DOI":"10.1016\/j.foodres.2006.03.006","volume":"39","author":"K Leon","year":"2006","unstructured":"Leon, K., Mery, D., Pedreschi, F., Leon, J.: Color measurement in lab units from RGB digital images. Food Res. Int. 39(10), 1084\u20131091 (2006)","journal-title":"Food Res. Int."},{"key":"37_CR25","doi-asserted-by":"crossref","unstructured":"MacDonald, L.: Color space transformation using neural networks. In: Color and Imaging Conference, vol. 2019, pp. 153\u2013158. Society for Imaging Science and Technology (2019)","DOI":"10.2352\/issn.2169-2629.2019.27.29"},{"key":"37_CR26","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.patrec.2019.12.008","volume":"131","author":"FLM Milotta","year":"2020","unstructured":"Milotta, F.L.M., et al.: Challenges in automatic Munsell color profiling for cultural heritage. Pattern Recogn. Lett. 131, 135\u2013141 (2020)","journal-title":"Pattern Recogn. Lett."},{"key":"37_CR27","unstructured":"Murmann, L., Gharbi, M., Aittala, M., Durand, F.: A multi-illumination dataset of indoor object appearance. In: 2019 IEEE International Conference on Computer Vision (ICCV) (2019)"},{"key":"37_CR28","doi-asserted-by":"publisher","unstructured":"Odena, A., Dumoulin, V., Olah, C.: Deconvolution and checkerboard artifacts. Distill (2016). https:\/\/doi.org\/10.23915\/distill.00003, http:\/\/distill.pub\/2016\/deconv-checkerboard","DOI":"10.23915\/distill.00003"},{"key":"37_CR29","doi-asserted-by":"crossref","unstructured":"Ruiz, J.F., Pereira, J.: The colours of rock art. Analysis of colour recording and communication systems in rock art research. J. Archaeol. Sci. 50, 338\u2013349 (2014)","DOI":"10.1016\/j.jas.2014.06.023"},{"issue":"6","key":"37_CR30","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1108\/00251740610673332","volume":"44","author":"S Singh","year":"2006","unstructured":"Singh, S.: Impact of color on marketing. Manage. Decis. 44(6), 783\u2013789 (2006)","journal-title":"Manage. Decis."},{"key":"37_CR31","unstructured":"S\u00f8nderby, C.K., Caballero, J., Theis, L., Shi, W., Husz\u00e1r, F.: Amortised map inference for image super-resolution. arXiv preprint: arXiv:1610.04490 (2016)"},{"key":"37_CR32","unstructured":"Stanco, F., Battiato, S., Gallo, G.: Digital Imaging for Cultural Heritage Preservation. Analysis, Restoration, and Reconstruction of Ancient Artworks (2011)"},{"key":"37_CR33","unstructured":"Theis, L., Shi, W., Cunningham, A., Husz\u00e1r, F.: Lossy image compression with compressive autoencoders. arXiv preprint: arXiv:1703.00395 (2017)"},{"key":"37_CR34","doi-asserted-by":"crossref","unstructured":"Velastegui, R., Pedersen, M.: CMYK-CIELAB color space transformation using machine learning techniques. In: London Imaging Meeting, vol. 2021, pp. 73\u201377. Society for Imaging Science and Technology (2021)","DOI":"10.2352\/issn.2694-118X.2021.LIM-73"}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Processing - ICIAP 2023 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-51026-7_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T05:14:59Z","timestamp":1711343699000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-51026-7_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031510250","9783031510267"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-51026-7_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"21 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image Analysis and Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Udine","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"11 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciap2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iciap2023.org\/","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"144","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":"82","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":"13","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":"57% - 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)"}},{"value":"https:\/\/iciap2023.org\/satellite-event\/workshops\/","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}