{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T02:44:42Z","timestamp":1775616282533,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T00:00:00Z","timestamp":1579651200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The capability of drones to perform autonomous missions has led retail companies to use them for deliveries, saving time and human resources. In these services, the delivery depends on the Global Positioning System (GPS) to define an approximate landing point. However, the landscape can interfere with the satellite signal (e.g., tall buildings), reducing the accuracy of this approach. Changes in the environment can also invalidate the security of a previously defined landing site (e.g., irregular terrain, swimming pool). Therefore, the main goal of this work is to improve the process of goods delivery using drones, focusing on the detection of the potential receiver. We developed a solution that has been improved along its iterative assessment composed of five test scenarios. The built prototype complements the GPS through Computer Vision (CV) algorithms, based on Convolutional Neural Networks (CNN), running in a Raspberry Pi 3 with a Pi NoIR Camera (i.e., No InfraRed\u2014without infrared filter). The experiments were performed with the models Single Shot Detector (SSD) MobileNet-V2, and SSDLite-MobileNet-V2. The best results were obtained in the afternoon, with the SSDLite architecture, for distances and heights between 2.5\u201310 m, with recalls from 59%\u201376%. The results confirm that a low computing power and cost-effective system can perform aerial human detection, estimating the landing position without an additional visual marker.<\/jats:p>","DOI":"10.3390\/s20030613","type":"journal-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T11:17:57Z","timestamp":1579691877000},"page":"613","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["UAV Landing Using Computer Vision Techniques for Human Detection"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5700-7893","authenticated-orcid":false,"given":"David","family":"Safadinho","sequence":"first","affiliation":[{"name":"School of Technology and Management, Computer Science and Communication Research Centre, Polytechnic Institute of Leiria, Campus 2, Morro do Lena \u2013 Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5361-9809","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Ramos","sequence":"additional","affiliation":[{"name":"School of Technology and Management, Computer Science and Communication Research Centre, Polytechnic Institute of Leiria, Campus 2, Morro do Lena \u2013 Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1547-4674","authenticated-orcid":false,"given":"Roberto","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"School of Technology and Management, Computer Science and Communication Research Centre, Polytechnic Institute of Leiria, Campus 2, Morro do Lena \u2013 Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3747-6577","authenticated-orcid":false,"given":"V\u00edtor","family":"Filipe","sequence":"additional","affiliation":[{"name":"INESC TEC and University of Tr\u00e1s-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4847-5104","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Barroso","sequence":"additional","affiliation":[{"name":"INESC TEC and University of Tr\u00e1s-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5062-1241","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Pereira","sequence":"additional","affiliation":[{"name":"School of Technology and Management, Computer Science and Communication Research Centre, Polytechnic Institute of Leiria, Campus 2, Morro do Lena \u2013 Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal"},{"name":"INOV INESC INOVA\u00c7\u00c3O, Institute of New Technologies, Leiria Office, Campus 2, Morro do Lena \u2013 Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4852","DOI":"10.1080\/01431161.2018.1490504","article-title":"The impact of small unmanned airborne platforms on passive optical remote sensing: A conceptual perspective","volume":"39","author":"Lippitt","year":"2018","journal-title":"Int. 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