{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T16:03:07Z","timestamp":1774454587441,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811611025","type":"print"},{"value":"9789811611032","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-1103-2_17","type":"book-chapter","created":{"date-parts":[[2021,3,25]],"date-time":"2021-03-25T08:03:32Z","timestamp":1616659412000},"page":"186-200","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Digital Borders: Design of an Animal Intrusion Detection System Based on\u00a0Deep Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9422-4002","authenticated-orcid":false,"given":"Prashanth C.","family":"Ravoor","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9032-7389","authenticated-orcid":false,"given":"T. S. B.","family":"Sudarshan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8162-6352","authenticated-orcid":false,"given":"Krishnan","family":"Rangarajan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,3,26]]},"reference":[{"issue":"11","key":"17_CR1","first-page":"1260","volume":"8","author":"S Angadi","year":"2019","unstructured":"Angadi, S., Katagall, R.: Agrivigilance: a security system for intrusion detection in agriculture using raspberry pi and openCV. Int. J. Sci. Technol. Res. 8(11), 1260\u20131267 (2019)","journal-title":"Int. J. Sci. Technol. Res."},{"key":"17_CR2","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778, June 2016. https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"17_CR3","unstructured":"Hermans, A., Beyer, L., Leibe, B.: In defense of the triplet loss for person re-identification. arXiv preprint arXiv:1703.07737 (2017)"},{"issue":"2","key":"17_CR4","first-page":"104","volume":"8","author":"K Sailesh","year":"2019","unstructured":"Sailesh, K., Balina, H.V., Sivakumar, T., Vijaya Poojitha, P.: Detection of wild elephants using image processing on raspberry pi3. Int. J. Comput. Sci. Mob. Comput. 8(2), 104\u2013115 (2019)","journal-title":"Int. J. Comput. Sci. Mob. Comput."},{"issue":"4","key":"17_CR5","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1080\/10871209.2017.1334106","volume":"22","author":"KK Karanth","year":"2017","unstructured":"Karanth, K.K., Kudalkar, S.: History, location, and species matter: insights for human-wildlife conflict mitigation from India. Hum. Dimens. Wildl. 22(4), 331\u2013346 (2017). https:\/\/doi.org\/10.1080\/10871209.2017.1334106","journal-title":"Hum. Dimens. Wildl."},{"issue":"7","key":"17_CR6","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1007\/s11263-020-01316-z","volume":"128","author":"A Kuznetsova","year":"2020","unstructured":"Kuznetsova, A., et al.: The open images dataset V4. Int. J. Comput. Vis. 128(7), 1956\u20131981 (2020)","journal-title":"Int. J. Comput. Vis."},{"key":"17_CR7","unstructured":"Kyari - The Nursery of Innovations: Animal intrusion detection and repellent system (2020). http:\/\/aniders.com\/"},{"key":"17_CR8","doi-asserted-by":"publisher","unstructured":"K\u00f6rschens, M., Denzler, J.: Elpephants: a fine-grained dataset for elephant re-identification. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 263\u2013270, October 2019. https:\/\/doi.org\/10.1109\/ICCVW.2019.00035","DOI":"10.1109\/ICCVW.2019.00035"},{"key":"17_CR9","unstructured":"K\u00f6rschens, M., Barz, B., Denzler, J.: Towards automatic identification of elephants in the wild. arXiv preprint arXiv:1812.04418 (2018)"},{"key":"17_CR10","unstructured":"Li, S., Li, J., Lin, W., Tang, H.: Amur tiger re-identification in the wild. arXiv preprint arXiv:1906.05586 (2019)"},{"key":"17_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"17_CR12","doi-asserted-by":"publisher","unstructured":"Liu, C., Zhang, R., Guo, L.: Part-pose guided amur tiger re-identification. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 315\u2013322 (2019). https:\/\/doi.org\/10.1109\/ICCVW.2019.00042","DOI":"10.1109\/ICCVW.2019.00042"},{"key":"17_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/978-3-319-46448-0_2","volume-title":"Computer Vision \u2013 ECCV 2016","author":"W Liu","year":"2016","unstructured":"Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21\u201337. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2"},{"key":"17_CR14","doi-asserted-by":"crossref","unstructured":"Luo, H., Gu, Y., Liao, X., Lai, S., Jiang, W.: Bag of tricks and a strong baseline for deep person re-identification. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, June 2019","DOI":"10.1109\/CVPRW.2019.00190"},{"key":"17_CR15","unstructured":"Ministry of Environment Forest and Climate Change: Human animal conflict, rajya sabha unstarred question no-222, February 2018. https:\/\/pqars.nic.in\/annex\/245\/Au222.pdf"},{"issue":"S","key":"17_CR16","first-page":"62","volume":"1","author":"G Pooja","year":"2016","unstructured":"Pooja, G., Bagal, M.U.: A smart farmland using raspberry pi crop vandalization prevention & intrusion detection system. Int. J. Adv. Res. Innov. Ideas Educ. 1(S), 62\u201368 (2016)","journal-title":"Int. J. Adv. Res. Innov. Ideas Educ."},{"key":"17_CR17","unstructured":"Prajna, P., Soujanya, B.S., Divya: IoT-based wild animal intrusion detection system. Int. J. Eng. Res. Technol. (IJERT) 6(15) (2018). https:\/\/www.ijert.org\/iot-based-wild-animal-intrusion-detection-system"},{"key":"17_CR18","doi-asserted-by":"publisher","first-page":"100289","DOI":"10.1016\/j.cosrev.2020.100289","volume":"38","author":"PC Ravoor","year":"2020","unstructured":"Ravoor, P.C., Sudarshan, T.S.B.: Deep learning methods for multi-species animal re-identification and tracking - a survey. Comput. Sci. Rev. 38, 100289 (2020). https:\/\/doi.org\/10.1016\/j.cosrev.2020.100289","journal-title":"Comput. Sci. Rev."},{"key":"17_CR19","unstructured":"Reddy, A., Vanamamalai, A., Gupta, S., Karanth, K.: Human-wildlife conflict in Karnataka (2020)"},{"key":"17_CR20","doi-asserted-by":"publisher","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 779\u2013788 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.91","DOI":"10.1109\/CVPR.2016.91"},{"issue":"6","key":"17_CR21","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"17_CR22","doi-asserted-by":"publisher","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.: MobileNetV 2: inverted residuals and linear bottlenecks. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4510\u20134520 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00474","DOI":"10.1109\/CVPR.2018.00474"},{"issue":"7","key":"17_CR23","doi-asserted-by":"publisher","first-page":"1757","DOI":"10.1109\/TPAMI.2012.256","volume":"35","author":"WJ Scheirer","year":"2013","unstructured":"Scheirer, W.J., de Rezende Rocha, A., Sapkota, A., Boult, T.E.: Toward open set recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35(7), 1757\u20131772 (2013). https:\/\/doi.org\/10.1109\/TPAMI.2012.256","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4S","key":"17_CR24","first-page":"307","volume":"7","author":"N Suganthi","year":"2018","unstructured":"Suganthi, N., Rajathi, N., Inzamam, M.F.: Elephant intrusion detection and repulsive system. Int. J. Recent Technol. Eng. 7(4S), 307\u2013310 (2018)","journal-title":"Int. J. Recent Technol. Eng."},{"key":"17_CR25","doi-asserted-by":"publisher","unstructured":"Xue, W., Jiang, T., Shi, J.: Animal intrusion detection based on convolutional neural network. In: 2017 17th International Symposium on Communications and Information Technologies (ISCIT), pp. 1\u20135 (2017). https:\/\/doi.org\/10.1109\/ISCIT.2017.8261234","DOI":"10.1109\/ISCIT.2017.8261234"}],"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\/978-981-16-1103-2_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T11:40:37Z","timestamp":1619264437000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-1103-2_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811611025","9789811611032"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-1103-2_17","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"26 March 2021","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":"Prayagraj","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":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cvip2020.iiita.ac.in","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"352","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":"134","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":"38% - 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":"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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was partially held in a virtual mode.","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)"}}]}}