{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T15:08:45Z","timestamp":1764688125257,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031840777"},{"type":"electronic","value":"9783031840784"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-84078-4_16","type":"book-chapter","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T19:06:09Z","timestamp":1741806369000},"page":"216-228","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["PetNet: Detection of\u00a0Diseases in\u00a0Dog Skin"],"prefix":"10.1007","author":[{"given":"Aldo","family":"Gomez-Lozano","sequence":"first","affiliation":[]},{"given":"Peter","family":"Montalvo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,13]]},"reference":[{"key":"16_CR1","unstructured":"American Veterinary Medical Association (AVMA): AVMA U. S. Pet Ownership and Demographics Sourcebook. American Veterinary Medical Association (2022)"},{"issue":"10","key":"16_CR2","doi-asserted-by":"publisher","first-page":"1248","DOI":"10.3346\/jkms.2012.27.10.1248","volume":"27","author":"JM Bae","year":"2012","unstructured":"Bae, J.M., Ha, B., Lee, H., Park, C.K., Kim, H.J., Park, Y.M.: Prevalence of common skin diseases and their associated factors among military personnel in Korea: a cross-sectional study. J. Korean Med. Sci. 27(10), 1248\u201354 (2012)","journal-title":"J. Korean Med. Sci."},{"key":"16_CR3","doi-asserted-by":"crossref","unstructured":"Bishop, C.M., Bishop, H.: Deep Learning - Foundations and Concepts. Springer, Heidelberg (2024)","DOI":"10.1007\/978-3-031-45468-4"},{"key":"16_CR4","doi-asserted-by":"publisher","first-page":"491","DOI":"10.3390\/e26060491","volume":"26","author":"R Connor","year":"2024","unstructured":"Connor, R., Dearle, A., Claydon, B., Vadicamo, L.: Correlations of cross-entropy loss in machine learning. Entropy 26, 491 (2024)","journal-title":"Entropy"},{"key":"16_CR5","doi-asserted-by":"crossref","unstructured":"Drechsler, Y., Dong, C., Clark, D., Kaur, G.: Canine atopic dermatitis: prevalence, impact, and management strategies. Veter. Med. (Auckland, N.Z.) 15, 15\u201329 (2024)","DOI":"10.2147\/VMRR.S412570"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Durrani, N., Sajjad, H., Dalvi, F.: How transfer learning impacts linguistic knowledge in deep NLP models? In: ACL\/IJCNLP (Findings). Findings of ACL, vol. ACL\/IJCNLP 2021, pp. 4947\u20134957. Association for Computational Linguistics (2021)","DOI":"10.18653\/v1\/2021.findings-acl.438"},{"key":"16_CR7","unstructured":"Gupta, D.: Image segmentation keras : implementation of segnet, fcn, unet, pspnet and other models in keras. CoRR arxiv:2307.13215 (2023)"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770\u2013778. IEEE Computer Society (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Hu, B., Song, R., Wei, X., Yao, Y., Hua, X., Liu, Y.: Pyretri: a pytorch-based library for unsupervised image retrieval by deep convolutional neural networks. In: ACM Multimedia, pp. 4461\u20134464. ACM (2020)","DOI":"10.1145\/3394171.3414537"},{"key":"16_CR10","doi-asserted-by":"crossref","unstructured":"Lozano-Mej\u00eda, D.J., Vega-Uribe, E.P., Ugarte, W.: Content-based image classification for sheet music books recognition. In: IEEE EIRCON (2020)","DOI":"10.1109\/EIRCON51178.2020.9254010"},{"issue":"17","key":"16_CR11","doi-asserted-by":"publisher","first-page":"26255","DOI":"10.1007\/s11042-021-10952-7","volume":"80","author":"MM Mijwil","year":"2021","unstructured":"Mijwil, M.M.: Skin cancer disease images classification using deep learning solutions. Multimedia Tools Appl. 80(17), 26255\u201326271 (2021)","journal-title":"Multimedia Tools Appl."},{"issue":"15","key":"16_CR12","doi-asserted-by":"publisher","first-page":"5652","DOI":"10.3390\/s22155652","volume":"22","author":"A Naeem","year":"2022","unstructured":"Naeem, A., Anees, T., Fiza, M., Naqvi, R.A., Lee, S.: Scdnet: a deep learning-based framework for the multiclassification of skin cancer using dermoscopy images. Sensors 22(15), 5652 (2022)","journal-title":"Sensors"},{"key":"16_CR13","doi-asserted-by":"publisher","first-page":"9797","DOI":"10.1007\/s13369-021-05571-1","volume":"46","author":"R Nersisson","year":"2021","unstructured":"Nersisson, R., Iyer, T., Joseph Raj, A.N., Rajangam, V.: A dermoscopic skin lesion classification technique using yolo-cnn and traditional feature model. Arab. J. Sci. Eng. 46, 9797\u20139808 (2021)","journal-title":"Arab. J. Sci. Eng."},{"key":"16_CR14","doi-asserted-by":"crossref","unstructured":"Rodrigues, J.P., Carbonera, J.L.: Graph convolutional networks for image classification: comparing approaches for building graphs from images. In: ICEIS (1), pp. 437\u2013446. SCITEPRESS (2024)","DOI":"10.5220\/0012263200003690"},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"Rodriguez-Meza, B., Vargas-Lopez-Lavalle, R., Ugarte, W.: Recurrent neural networks for deception detection in videos. In: ICAT (2022)","DOI":"10.1007\/978-3-031-03884-6_29"},{"key":"16_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2020.103074","volume":"76","author":"T Shanthi","year":"2020","unstructured":"Shanthi, T., Sabeenian, R.S., Anand, R.: Automatic diagnosis of skin diseases using convolution neural network. Microprocess. Microsyst. 76, 103074 (2020)","journal-title":"Microprocess. Microsyst."},{"key":"16_CR17","doi-asserted-by":"crossref","unstructured":"Ysique-Neciosup, J., Chavez, N.M., Ugarte, W.: Deephistory: a convolutional neural network for automatic animation of museum paintings. Comput. Animat. Virtual Worlds 33(5) (2022)","DOI":"10.1002\/cav.2110"}],"container-title":["Communications in Computer and Information Science","Advanced Research in Technologies, Information, Innovation and Sustainability"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-84078-4_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T19:06:16Z","timestamp":1741806376000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-84078-4_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031840777","9783031840784"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-84078-4_16","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"13 March 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ARTIIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Santiago de Chile","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chile","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":"20 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 October 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":"artiis2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.artiis.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}