{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T07:12:49Z","timestamp":1776496369599,"version":"3.51.2"},"reference-count":37,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"\u00abICT-based wild animal census approach for sustainable wildlife management\u00bb (1.1.1.1\/18\/A\/146) co-funded by the European Regional Development Fund 1.1.1.1. measure \u201cSupport for applied research\u201d","award":["1.1.1.1\/18\/A\/146"],"award-info":[{"award-number":["1.1.1.1\/18\/A\/146"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Changes in the ungulate population density in the wild has impacts on both the wildlife and human society. In order to control the ungulate population movement, monitoring systems such as camera trap networks have been implemented in a non-invasive setup. However, such systems produce a large number of images as the output, hence making it very resource consuming to manually detect the animals. In this paper, we present a new dataset of wild ungulates which was collected in Latvia. Moreover, we demonstrate two methods, which use RetinaNet and Faster R-CNN as backbones, respectively, to detect the animals in the images. We discuss the optimization of training and impact of data augmentation on the performance. Finally, we show the result of aforementioned tune networks over the real world data collected in Latvia.<\/jats:p>","DOI":"10.3390\/e24030353","type":"journal-article","created":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T20:09:57Z","timestamp":1646078997000},"page":"353","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["Ungulate Detection and Species Classification from Camera Trap Images Using RetinaNet and Faster R-CNN"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1233-764X","authenticated-orcid":false,"given":"Alekss","family":"Vecvanags","sequence":"first","affiliation":[{"name":"Institute for Environmental Solutions, LV-4126 C\u0113sis, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kadir","family":"Aktas","sequence":"additional","affiliation":[{"name":"iCV Lab, Institute of Technology, University of Tartu, 51009 Tartu, Estonia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilja","family":"Pavlovs","sequence":"additional","affiliation":[{"name":"iCV Lab, Institute of Technology, University of Tartu, 51009 Tartu, Estonia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Egils","family":"Avots","sequence":"additional","affiliation":[{"name":"iCV Lab, Institute of Technology, University of Tartu, 51009 Tartu, Estonia"},{"name":"Forest Owners Consulting Center LCC, LV-4101 C\u0113sis, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jevgenijs","family":"Filipovs","sequence":"additional","affiliation":[{"name":"Institute for Environmental Solutions, LV-4126 C\u0113sis, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8011-3125","authenticated-orcid":false,"given":"Agris","family":"Brauns","sequence":"additional","affiliation":[{"name":"Institute for Environmental Solutions, LV-4126 C\u0113sis, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gundega","family":"Done","sequence":"additional","affiliation":[{"name":"Latvian State Forest Research Institute \u201cSilava\u201d, LV-2169 Salaspils, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2969-5972","authenticated-orcid":false,"given":"Dainis","family":"Jakovels","sequence":"additional","affiliation":[{"name":"Institute for Environmental Solutions, LV-4126 C\u0113sis, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8460-5717","authenticated-orcid":false,"given":"Gholamreza","family":"Anbarjafari","sequence":"additional","affiliation":[{"name":"Institute for Environmental Solutions, LV-4126 C\u0113sis, Latvia"},{"name":"iCV Lab, Institute of Technology, University of Tartu, 51009 Tartu, Estonia"},{"name":"PwC Advisory, 00180 Helsinki, Finland"},{"name":"Faculty of Engineering, Hasan Kalyoncu University, Gaziantep 27410, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1111\/mam.12202","article-title":"Overabundant wild ungulate populations in Europe: Management with consideration of socio-ecological consequences","volume":"50","author":"Valente","year":"2020","journal-title":"Mammal Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1111\/mam.12221","article-title":"Wild ungulate overabundance in Europe: Contexts, causes, monitoring and management recommendations","volume":"51","author":"Carpio","year":"2021","journal-title":"Mammal Rev."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Langbein, J., Putman, R., and Pokorny, B. 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