{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T06:29:17Z","timestamp":1776407357844,"version":"3.51.2"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031581731","type":"print"},{"value":"9783031581748","type":"electronic"}],"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\/978-3-031-58174-8_22","type":"book-chapter","created":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T09:07:37Z","timestamp":1719911257000},"page":"252-262","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["xDFPAD: Explainable Tabular Deep Learning for\u00a0Fingerprint Presentation Attack Detection"],"prefix":"10.1007","author":[{"given":"Shaik","family":"Dastagiri","sequence":"first","affiliation":[]},{"given":"Kongara","family":"Sireesh","sequence":"additional","affiliation":[]},{"given":"Ram Prakash","family":"Sharma","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,3]]},"reference":[{"key":"22_CR1","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.patrec.2021.03.032","volume":"147","author":"S Agarwal","year":"2021","unstructured":"Agarwal, S., Rattani, A., Chowdary, C.R.: A comparative study on handcrafted features v\/s deep features for open-set fingerprint liveness detection. Pattern Recogn. Lett. 147, 34\u201340 (2021)","journal-title":"Pattern Recogn. Lett."},{"key":"22_CR2","doi-asserted-by":"crossref","unstructured":"Anusha, B., Banerjee, S., Chaudhuri, S.: DeFraudNet:End2End fingerprint spoof detection using patch level attention. In: 2020 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 2684\u20132693 (2020)","DOI":"10.1109\/WACV45572.2020.9093397"},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"Arik, S., Pfister, T.: TabNet: attentive interpretable tabular learning. In: AAAI Conference on Artificial Intelligence, vol.\u00a035, pp. 6679\u20136687 (2019)","DOI":"10.1609\/aaai.v35i8.16826"},{"issue":"9","key":"22_CR4","doi-asserted-by":"publisher","first-page":"2190","DOI":"10.1109\/TIFS.2018.2812193","volume":"13","author":"T Chugh","year":"2018","unstructured":"Chugh, T., Cao, K., Jain, A.K.: Fingerprint spoof buster: use of minutiae-centered patches. IEEE Trans. Inf. Forensics Secur. 13(9), 2190\u20132202 (2018)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"22_CR5","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1109\/TIFS.2020.2990789","volume":"16","author":"T Chugh","year":"2021","unstructured":"Chugh, T., Jain, A.K.: Fingerprint spoof detector generalization. IEEE Trans. Inf. Forensics Secur. 16, 42\u201355 (2021)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"22_CR6","doi-asserted-by":"crossref","unstructured":"Frassetto\u00a0Nogueira, R., de\u00a0Alencar\u00a0Lotufo, R., Campos\u00a0Machado, R.: Evaluating software-based fingerprint liveness detection using convolutional networks and local binary patterns. In: 2014 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS) Proceedings, pp. 22\u201329 (2014)","DOI":"10.1109\/BIOMS.2014.6951531"},{"key":"22_CR7","unstructured":"ISO\/IEC3010-3: Information technology \u2013 biometric presentation attack detection\u2014part 3: Testing and reporting (2023)"},{"issue":"9","key":"22_CR8","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1049\/el.2018.0621","volume":"54","author":"H Jung","year":"2018","unstructured":"Jung, H., Heo, Y.: Fingerprint liveness map construction using convolutional neural network. Electron. Lett. 54(9), 564\u2013566 (2018)","journal-title":"Electron. Lett."},{"key":"22_CR9","doi-asserted-by":"crossref","unstructured":"Olsen, M., \u0160mida, V., Busch, C.: Finger image quality assessment features - definitions and evaluation. IET Biometrics 5 (2016)","DOI":"10.1049\/iet-bmt.2014.0055"},{"key":"22_CR10","doi-asserted-by":"crossref","unstructured":"Park, E., Kim, W., Li, Q., Kim, J., Kim, H.: Fingerprint liveness detection using CNN features of random sample patches. In: 2016 International Conference of the Biometrics Special Interest Group (BIOSIG), pp.\u00a01\u20134 (2016)","DOI":"10.1109\/BIOSIG.2016.7736923"},{"key":"22_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1007\/978-3-030-66187-8","volume-title":"Mining Intelligence and Knowledge Exploration","author":"RP Sharma","year":"2020","unstructured":"Sharma, R.P., Anshul, A., Jha, A., Dey, S.: Investigating fingerprint quality features for liveness detection. In: Purushothama, B.R., Thenkanidiyoor, V., Prasath, R., Vanga, O. (eds.) MIKE 2019. LNCS, vol. 11987, pp. 296\u2013307. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-66187-8"},{"key":"22_CR12","doi-asserted-by":"publisher","first-page":"1393","DOI":"10.1007\/s00371-018-01618-x","volume":"35","author":"R Sharma","year":"2019","unstructured":"Sharma, R., Dey, S.: Fingerprint liveness detection using local quality features. Vis. Comput. 35, 1393\u20131410 (2019)","journal-title":"Vis. Comput."},{"key":"22_CR13","doi-asserted-by":"publisher","first-page":"9993","DOI":"10.1007\/s11042-020-10136-9","volume":"80","author":"R Sharma","year":"2021","unstructured":"Sharma, R., Dey, S.: A comparative study of handcrafted local texture descriptors for fingerprint liveness detection under real world scenarios. Multimed. Tools Appl. 80, 9993\u201310012 (2021)","journal-title":"Multimed. Tools Appl."},{"key":"22_CR14","doi-asserted-by":"crossref","unstructured":"Toosi, A., Cumani, S., Bottino, A.: CNN patch-based voting for fingerprint liveness detection. In: International Joint Conference on Computational Intelligence (2017)","DOI":"10.5220\/0006582101580165"},{"issue":"2","key":"22_CR15","first-page":"264","volume":"23","author":"DM Uliyan","year":"2020","unstructured":"Uliyan, D.M., Sadeghi, S., Jalab, H.A.: Anti-spoofing method for fingerprint recognition using patch based deep learning machine. Int. J. Eng. Sci. Technol. 23(2), 264\u2013273 (2020)","journal-title":"Int. J. Eng. Sci. Technol."},{"key":"22_CR16","doi-asserted-by":"crossref","unstructured":"Wang, C., Li, K., Wu, Z., Zhao, Q.: A DCNN based fingerprint liveness detection algorithm with voting strategy. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds.) Biometric Recognition, pp. 241\u2013249 (2015)","DOI":"10.1007\/978-3-319-25417-3_29"},{"key":"22_CR17","doi-asserted-by":"publisher","first-page":"183391","DOI":"10.1109\/ACCESS.2020.3027846","volume":"8","author":"Y Zhang","year":"2020","unstructured":"Zhang, Y., Gao, C., Pan, S., Li, Z., Xu, Y., Qiu, H.: A score-level fusion of fingerprint matching with fingerprint liveness detection. IEEE Access 8, 183391\u2013183400 (2020)","journal-title":"IEEE Access"},{"key":"22_CR18","doi-asserted-by":"publisher","first-page":"84141","DOI":"10.1109\/ACCESS.2020.2990909","volume":"8","author":"Y Zhang","year":"2020","unstructured":"Zhang, Y., Pan, S., Zhan, X., Li, Z., Gao, M., Gao, C.: FLDNet: light dense CNN for fingerprint liveness detection. IEEE Access 8, 84141\u201384152 (2020)","journal-title":"IEEE Access"},{"key":"22_CR19","doi-asserted-by":"publisher","first-page":"91476","DOI":"10.1109\/ACCESS.2019.2927357","volume":"7","author":"Y Zhang","year":"2019","unstructured":"Zhang, Y., Shi, D., Zhan, X., Cao, D., Zhu, K., Li, Z.: Slim-ResCNN: a deep residual convolutional neural network for fingerprint liveness detection. IEEE Access 7, 91476\u201391487 (2019)","journal-title":"IEEE Access"}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-58174-8_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T09:13:04Z","timestamp":1719911584000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-58174-8_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031581731","9783031581748"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-58174-8_22","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jammu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","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":"3 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iitjammu.ac.in\/cvip2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Online CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"461","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":"140","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":"30% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}