{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:09:51Z","timestamp":1760231391179,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,17]],"date-time":"2022-09-17T00:00:00Z","timestamp":1663372800000},"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>This paper proposes a photoelectric target detection algorithm for NVIDIA Jeston Nano embedded devices, exploiting the characteristics of active and passive differential images of lasers after denoising. An adaptive threshold segmentation method was developed based on the statistical characteristics of photoelectric target echo light intensity, which effectively improves detection of the target area. The proposed method\u2019s effectiveness is compared and analyzed against a typical lightweight network that was knowledge-distilled by ResNet18 on target region detection tasks. Furthermore, TensorRT technology was applied to accelerate inference and deploy on hardware platforms the lightweight network Shuffv2_x0_5. The experimental results demonstrate that the developed method\u2019s accuracy rate reaches 97.15%, the false alarm rate is 4.87%, and the detection rate can reach 29 frames per second for an image resolution of 640 \u00d7 480 pixels.<\/jats:p>","DOI":"10.3390\/s22187053","type":"journal-article","created":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T04:49:22Z","timestamp":1663562962000},"page":"7053","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Photoelectric Target Detection Algorithm Based on NVIDIA Jeston Nano"],"prefix":"10.3390","volume":"22","author":[{"given":"Shicheng","family":"Zhang","sequence":"first","affiliation":[{"name":"Graduate School, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laixian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huayan","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huichao","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"040004","DOI":"10.3788\/LOP50.040004","article-title":"Progress of Free-Space Optical Communication Technology Based on Modulating Retro-Reflector","volume":"50","author":"Huayan","year":"2013","journal-title":"Laser Optoelectron. 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