{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T16:54:24Z","timestamp":1743008064895,"version":"3.40.3"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031774256"},{"type":"electronic","value":"9783031774263"}],"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\/978-3-031-77426-3_12","type":"book-chapter","created":{"date-parts":[[2024,12,25]],"date-time":"2024-12-25T08:07:52Z","timestamp":1735114072000},"page":"173-188","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Neural Network-Based Approach to\u00a0Identifying Wrinkles and\u00a0Recommending Cosmetic Products"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0497-4309","authenticated-orcid":false,"given":"Guilherme","family":"de M. Tonello","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6323-0071","authenticated-orcid":false,"given":"Maria Jo\u00e3o Varanda","family":"Pereira","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0100-8691","authenticated-orcid":false,"given":"Paulo","family":"Alves","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9622-8525","authenticated-orcid":false,"given":"Andr\u00e9","family":"Roberto Ortoncelli","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,26]]},"reference":[{"key":"12_CR1","doi-asserted-by":"crossref","unstructured":"Alrabiah, A., Alduailij, M., Crane, M.: Computer-based approach to detect wrinkles and suggest facial fillers. Int. J. Adv. Comput. Sci. Appl. 10(9) (2019)","DOI":"10.14569\/IJACSA.2019.0100941"},{"key":"12_CR2","unstructured":"Aquavalor: Aquae vitae \u2013 \u00c1gua termal como fonte de vida e sa\u00fade (2022). https:\/\/aquavalor.pt\/2022\/03\/29\/aquae-vitae-agua-termal-como-fonte-de-vida-e-saude\/"},{"issue":"3","key":"12_CR3","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1016\/j.patcog.2014.08.003","volume":"48","author":"N Batool","year":"2015","unstructured":"Batool, N., Chellappa, R.: Fast detection of facial wrinkles based on gabor features using image morphology and geometric constraints. Pattern Recogn. 48(3), 642\u2013658 (2015)","journal-title":"Pattern Recogn."},{"key":"12_CR4","unstructured":"Caliva, F., Iriondo, C., Martinez, A.M., Majumdar, S., Pedoia, V.: Distance map loss penalty term for semantic segmentation. arXiv preprint arXiv:1908.03679 (2019)"},{"key":"12_CR5","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.eswa.2018.07.026","volume":"114","author":"E Cetinic","year":"2018","unstructured":"Cetinic, E., Lipic, T., Grgic, S.: Fine-tuning convolutional neural networks for fine art classification. Expert Syst. Appl. 114, 107\u2013118 (2018)","journal-title":"Expert Syst. Appl."},{"key":"12_CR6","unstructured":"Chen, H.F., Lee, Y.H., Tu, Y.C., Chao, Y.F.: Consumer purchase intention for skincare products (2012)"},{"issue":"11","key":"12_CR7","doi-asserted-by":"publisher","first-page":"3922","DOI":"10.3390\/su10113922","volume":"10","author":"J Chin","year":"2018","unstructured":"Chin, J., Jiang, B.C., Mufidah, I., Persada, S.F., Noer, B.A.: The investigation of consumers\u2019 behavior intention in using green skincare products: a pro-environmental behavior model approach. Sustainability 10(11), 3922 (2018)","journal-title":"Sustainability"},{"key":"12_CR8","unstructured":"Deeptag: Deeptag AI. https:\/\/deeptag.ai\/DeepTagPage.html"},{"key":"12_CR9","unstructured":"Dermalogica: Dermalogica face mapping. https:\/\/www.dermalogica.co.uk\/pages\/face-mapping"},{"key":"12_CR10","unstructured":"Garnier: Skin coach AI. https:\/\/www.garnier.com.au\/skin-coach-skin-analysis"},{"key":"12_CR11","unstructured":"Groupe, L.: Skinconsult AI vichy. https:\/\/www.loreal.com\/en\/articles\/science-and-technology\/skinconsult-ai-vichy\/"},{"key":"12_CR12","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.patcog.2017.10.013","volume":"77","author":"J Gu","year":"2018","unstructured":"Gu, J., et al.: Recent advances in convolutional neural networks. Pattern Recogn. 77, 354\u2013377 (2018)","journal-title":"Pattern Recogn."},{"key":"12_CR13","unstructured":"Haut.AI: Hautai \u2013 AI skin analysis. https:\/\/haut.ai"},{"key":"12_CR14","unstructured":"Ignae: Ai skin analysis. https:\/\/ignae.com\/pages\/ai-skin-analysis"},{"key":"12_CR15","doi-asserted-by":"crossref","unstructured":"Kim, S., Yoon, H., Lee, J., Yoo, S.: Semi-automatic labeling and training strategy for deep learning-based facial wrinkle detection. In: IEEE International Symposium on Computer-based Medical Systems (CBMS), pp. 383\u2013388. IEEE (2022)","DOI":"10.1109\/CBMS55023.2022.00075"},{"key":"12_CR16","unstructured":"Kokoi, I.: Female buying behaviour related to facial skin care products (2011)"},{"issue":"5","key":"12_CR17","doi-asserted-by":"publisher","first-page":"375","DOI":"10.5021\/ad.2020.32.5.375","volume":"32","author":"YB Lee","year":"2020","unstructured":"Lee, Y.B., et al.: Perceptions and behavior regarding skin health and skin care products: analysis of the questionnaires for the visitors of skin health expo 2018. Ann. Dermatol. 32(5), 375 (2020)","journal-title":"Ann. Dermatol."},{"key":"12_CR18","doi-asserted-by":"crossref","unstructured":"Liu, Z., Qi, Q., Wang, S., Zhai, G.: A novel approach to the detection of facial wrinkles: database, detection algorithm, and evaluation metrics. Comput. Biol. Med. 108431 (2024)","DOI":"10.1016\/j.compbiomed.2024.108431"},{"key":"12_CR19","unstructured":"Lugaresi, C., et\u00a0al.: Mediapipe: a framework for perceiving and processing reality. In: Workshop on Computer Vision for AR\/VR at IEEE Computer Vision and Pattern Recognition (CVPR), vol.\u00a02019 (2019)"},{"key":"12_CR20","unstructured":"Lululab: Lumini software development kit. https:\/\/www.lulu-lab.com\/"},{"key":"12_CR21","doi-asserted-by":"crossref","unstructured":"Ng, C.C., Yap, M.H., Costen, N., Li, B.: Automatic wrinkle detection using hybrid hessian filter. In: Asian Conference on Computer Vision, pp. 609\u2013622. Springer (2015)","DOI":"10.1007\/978-3-319-16811-1_40"},{"key":"12_CR22","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1109\/ACCESS.2015.2455871","volume":"3","author":"CC Ng","year":"2015","unstructured":"Ng, C.C., Yap, M.H., Costen, N., Li, B.: Wrinkle detection using hessian line tracking. IEEE Access 3, 1079\u20131088 (2015)","journal-title":"IEEE Access"},{"issue":"10","key":"12_CR23","doi-asserted-by":"publisher","first-page":"1090","DOI":"10.1109\/34.879790","volume":"22","author":"PJ Phillips","year":"2000","unstructured":"Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The feret evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1090\u20131104 (2000)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"12_CR24","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/S0262-8856(97)00070-X","volume":"16","author":"PJ Phillips","year":"1998","unstructured":"Phillips, P.J., Wechsler, H., Huang, J., Rauss, P.J.: The feret database and evaluation procedure for face-recognition algorithms. Image Vis. Comput. 16(5), 295\u2013306 (1998)","journal-title":"Image Vis. Comput."},{"key":"12_CR25","doi-asserted-by":"publisher","unstructured":"Poojary, R., Pai, A.: Comparative study of model optimization techniques in fine-tuned CNN models. In: International Conference on Electrical and Computing Technologies and Applications (ICECTA), pp.\u00a01\u20134 (2019). https:\/\/doi.org\/10.1109\/ICECTA48151.2019.8959681","DOI":"10.1109\/ICECTA48151.2019.8959681"},{"key":"12_CR26","unstructured":"Revieve: Ai skin diagnostics. https:\/\/www.revieve.com\/platform\/skincare\/ai-skin-diagnostics"},{"key":"12_CR27","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Medical Image Computing and computer-Assisted Intervention (MICCAI), pp. 234\u2013241. Springer (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"12_CR28","doi-asserted-by":"publisher","unstructured":"Serengil, S.I., Ozpinar, A.: Hyperextended lightface: a facial attribute analysis framework. In: International Conference on Engineering and Emerging Technologies (ICEET), pp.\u00a01\u20134. IEEE (2021). https:\/\/doi.org\/10.1109\/ICEET53442.2021.9659697, https:\/\/ieeexplore.ieee.org\/document\/9659697","DOI":"10.1109\/ICEET53442.2021.9659697"},{"key":"12_CR29","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"12_CR30","unstructured":"SkinQ: Skinq AI mirror. https:\/\/skinq.com\/pages\/ai-mirror"},{"key":"12_CR31","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818\u20132826 (2016)","DOI":"10.1109\/CVPR.2016.308"},{"key":"12_CR32","unstructured":"TensorFlow: an end-to-end platform for machine learning. https:\/\/www.tensorflow.org\/"},{"key":"12_CR33","doi-asserted-by":"publisher","first-page":"196197","DOI":"10.1109\/ACCESS.2020.3034343","volume":"8","author":"G Vrban\u010di\u010d","year":"2020","unstructured":"Vrban\u010di\u010d, G., Podgorelec, V.: Transfer learning with adaptive fine-tuning. IEEE Access 8, 196197\u2013196211 (2020)","journal-title":"IEEE Access"},{"issue":"1","key":"12_CR34","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1111\/j.1600-0781.2007.00262.x","volume":"23","author":"N Yusuf","year":"2007","unstructured":"Yusuf, N., Irby, C., Katiyar, S.K., Elmets, C.A.: Photoprotective effects of green tea polyphenols. Photodermatology, photoimmunology photomedicine 23(1), 48\u201356 (2007)","journal-title":"Photodermatology, photoimmunology photomedicine"},{"issue":"10","key":"12_CR35","doi-asserted-by":"publisher","first-page":"1499","DOI":"10.1109\/LSP.2016.2603342","volume":"23","author":"K Zhang","year":"2016","unstructured":"Zhang, K., Zhang, Z., Li, Z., Qiao, Y.: Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Process. Lett. 23(10), 1499\u20131503 (2016)","journal-title":"IEEE Signal Process. Lett."}],"container-title":["Communications in Computer and Information Science","Optimization, Learning Algorithms and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-77426-3_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,25]],"date-time":"2024-12-25T09:04:45Z","timestamp":1735117485000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-77426-3_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031774256","9783031774263"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-77426-3_12","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"26 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Author Guilherme Tonello has received research grants from \u201cFunda\u00e7\u00e3o La Caixa\u201d and by \u201cFunda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia\u201d under the scope of the project \u201cAquae Vitae \u2013 \u00c1gua Termal como Fonte de Vida e Sa\u00fade\u201d.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"OL2A","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Optimization, Learning Algorithms and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tenerife","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ol2a2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ol2a.ipb.pt\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}