{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T18:34:23Z","timestamp":1763058863472,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T00:00:00Z","timestamp":1675728000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the region Grand Est"},{"name":"bank \u201cCredit Agricole\u2014Champagne Bourgogne Branch\u201d"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Early detection of physical frailty and infectious diseases in seniors is important to avoid any fatal drawback and promptly provide them with the necessary healthcare. One of the major symptoms of viral infections is elevated body temperature. In this work, preparation and implementation of multi-age thermal faces dataset is done to train different \u201cYou Only Look Once\u201d (YOLO) object detection models (YOLOv5,6 and 7) for eye detection. Eye detection allows scanning for the most accurate temperature in the face, which is the inner canthus temperature. An approach using an elderly thermal dataset is performed in order to produce an eye detection model specifically for elderly people. An application of transfer learning is applied from a multi-age YOLOv7 model to an elderly YOLOv7 model. The comparison of speed, accuracy, and size between the trained models shows that the YOLOv7 model performed the best (Mean average precision at Intersection over Union of 0.5 (mAP@.5) = 0.996 and Frames per Seconds (FPS) = 150). The bounding box of eyes is scanned for the highest temperature, resulting in a normalized error distance of 0.03. This work presents a fast and reliable temperature detection model generated using non-contact infrared camera and a deep learning approach.<\/jats:p>","DOI":"10.3390\/s23041851","type":"journal-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T02:04:16Z","timestamp":1675821856000},"page":"1851","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Eye Recognition by YOLO for Inner Canthus Temperature Detection in the Elderly Using a Transfer Learning Approach"],"prefix":"10.3390","volume":"23","author":[{"given":"Malak","family":"Ghourabi","sequence":"first","affiliation":[{"name":"Computer Science and Digital Society (LIST3N), University of Technology of Troyes, 10000 Troyes, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5048-9372","authenticated-orcid":false,"given":"Farah","family":"Mourad-Chehade","sequence":"additional","affiliation":[{"name":"Computer Science and Digital Society (LIST3N), University of Technology of Troyes, 10000 Troyes, France"}]},{"given":"Aly","family":"Chkeir","sequence":"additional","affiliation":[{"name":"Computer Science and Digital Society (LIST3N), University of Technology of Troyes, 10000 Troyes, France"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,7]]},"reference":[{"key":"ref_1","unstructured":"Joinup (2022, September 20). EU: Together for Health: A Strategic Approach for the EU 2008\u20132013. Available online: https:\/\/joinup.ec.europa.eu\/collection\/ehealth\/document\/eu-together-health-strategic-approach-eu-2008-2013."},{"key":"ref_2","unstructured":"(2022, December 01). Haut Conseil de la Sant\u00e9 Publique, \u201cCoronavirus SARS-CoV-2: Personnes \u00e0 Risque de Formes S\u00e9v\u00e8res\u201d. Available online: https:\/\/www.hcsp.fr\/Explore.cgi\/avisrapportsdomaine?clefr=904."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e444","DOI":"10.1016\/S2468-2667(20)30146-8","article-title":"The effect of frailty on survival in patients with COVID-19 (COPE): A multicentre, European, observational cohort study","volume":"5","author":"Hewitt","year":"2020","journal-title":"Lancet Public Health"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1752","DOI":"10.1111\/jth.14828","article-title":"Tissue plasminogen activator (tPA) treatment for COVID-19 associated acute respiratory distress syndrome (ARDS): A case series","volume":"18","author":"Wang","year":"2020","journal-title":"J. Thromb. Haemost."},{"key":"ref_5","unstructured":"Imaz Press R\u00e9union (2022, December 01). Detecter le Virus Avant tout Symptome Grace aux Accessoires Connectes. Available online: http:\/\/www.ipreunion.com\/france-monde\/reportage\/2020\/06\/07\/detecter-le-virus-avant-tout-symptome-grace-aux-accessoires-connectes,120008.html."},{"key":"ref_6","unstructured":"World Health Organization (2022, December 01). Coronavirus Disease (COVID-19). Available online: https:\/\/www.who.int\/emergencies\/diseases\/novel-coronavirus-2019\/question-and-answers-hub\/q-a-detail\/coronavirus-disease-covid-19."},{"key":"ref_7","unstructured":"U.S. Food and Drug Administration (2022, December 01). Non-Contact Temperature Assessment Devices during the COVID-19 Pandemic, Available online: https:\/\/www.fda.gov\/medical-devices\/coronavirus-covid-19-and-medical-devices\/non-contact-temperature-assessment-devices-during-covid-19-pandemic#:~:text=contact%20Infrared%20Thermometers-,Benefits%20of%20Non%2Dcontact%20Temperature%20Assessment%20Devices,require%20minimal%20cleaning%20between%20uses."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.infrared.2012.03.007","article-title":"Medical applications of infrared thermography: A review","volume":"55","author":"Lahiri","year":"2012","journal-title":"Infrared Phys. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"094001","DOI":"10.1088\/1361-6579\/ab2af6","article-title":"Bilateral assessment of body core temperature through axillar, tympanic and inner canthi thermometers in a young population","volume":"40","author":"Vardasca","year":"2019","journal-title":"Physiol. Meas."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zou, X. (2019, January 10\u201311). A Review of Object Detection Techniques. Proceedings of the 2019 International Conference on Smart Grid and Electrical Automation (ICSGEA), Xiangtan, China.","DOI":"10.1109\/ICSGEA.2019.00065"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1066","DOI":"10.1016\/j.procs.2022.01.135","article-title":"A Review of Yolo Algorithm Developments","volume":"199","author":"Jiang","year":"2022","journal-title":"Procedia Comput. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Hussien, M.N., Lye, M.-H., Fauzi, M.F.A., Seong, T.C., and Mansor, S. (2017, January 12\u201314). Comparative analysis of eyes detection on face thermal images. Proceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), Kuching, Malaysia.","DOI":"10.1109\/ICSIPA.2017.8120641"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2570","DOI":"10.18517\/ijaseit.8.6.3903","article-title":"Inner-Canthus Localization of Thermal Images in Face-View Invariant","volume":"8","author":"Fitriyah","year":"2018","journal-title":"Int. J. Adv. Sci. Eng. Inf. Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3601","DOI":"10.1007\/s11042-020-09403-6","article-title":"Fast eyes detection in thermal images","volume":"80","author":"Knapik","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_15","unstructured":"T\u00fcrk\u00e7etin, A., Nasibli, H., and \u015eahan, M. (2021, January 23\u201327). Fever Detection from Human Thermal Images with Deep Learning Methods. Proceedings of the 7th International Conference on Engineering and Natural Sciences (ICENS), Sarajevo, Bosnia and Herzegovina."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.infrared.2013.05.007","article-title":"Face and eyes localization algorithm in thermal images for temperature measurement of the inner canthus of the eyes","volume":"60","author":"Budzan","year":"2013","journal-title":"Infrared Phys. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ferrari, C., Berlincioni, L., Bertini, M., and del Bimbo, A. (2021, January 10\u201315). Inner Eye Canthus Localization for Human Body Temperature Screening. Proceedings of the 2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy.","DOI":"10.1109\/ICPR48806.2021.9412015"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"39080","DOI":"10.1109\/ACCESS.2022.3161968","article-title":"Detecting Essential Landmarks Directly in Thermal Images for Remote Body Temperature and Respiratory Rate Measurement With a Two-Phase System","volume":"10","author":"Lazri","year":"2022","journal-title":"IEEE Access"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"805669","DOI":"10.3389\/fninf.2021.805669","article-title":"Deep Learning in Large and Multi-Site Structural Brain MR Imaging Datasets","volume":"15","author":"Bento","year":"2022","journal-title":"Front. Neuroinform."},{"key":"ref_20","first-page":"130","article-title":"The influence of angles and distance on assessing inner-canthi of the eye skin temperature","volume":"27","author":"Vardasca","year":"2017","journal-title":"Thermol. Int."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2084","DOI":"10.1109\/TIFS.2022.3177949","article-title":"TFW: Annotated Thermal Faces in the Wild Dataset","volume":"17","author":"Kuzdeuov","year":"2022","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_22","unstructured":"(2022, December 01). The Tufts Face Database. Available online: http:\/\/tdface.ece.tufts.edu\/."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1109\/TPAMI.2018.2884458","article-title":"A comprehensive database for benchmarking imaging systems","volume":"42","author":"Panetta","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Kopaczka, M., Kolk, R., and Merhof, D. (2018, January 14\u201317). A fully annotated thermal face database and its application for thermal facial expression recognition. Proceedings of the 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Houston, TX, USA.","DOI":"10.1109\/I2MTC.2018.8409768"},{"key":"ref_25","unstructured":"(2022, December 01). Roboflow. Available online: https:\/\/app.roboflow.com."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1186\/s40537-019-0197-0","article-title":"A survey on Image Data Augmentation for Deep Learning","volume":"6","author":"Shorten","year":"2019","journal-title":"J. Big Data"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016, January 27\u201330). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1798","DOI":"10.1002\/lary.29960","article-title":"Deep Learning Applied to White Light and Narrow Band Imaging Videolaryngoscopy: Toward Real-Time Laryngeal Cancer Detection","volume":"132","author":"Azam","year":"2022","journal-title":"Laryngoscope"},{"key":"ref_29","first-page":"333","article-title":"Investigation of yolov5 efficiency in iPhone supported systems","volume":"9","year":"2021","journal-title":"Balt. J. Mod. Comput."},{"key":"ref_30","unstructured":"GitHub (2022, December 01). Train Custom Data ultralytics\/yolov5 Wiki. Available online: https:\/\/github.com\/ultralytics\/yolov5\/wiki\/Train-Custom-Data."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Snegireva, D., and Perkova, A. (2021, January 5\u201311). Traffic Sign Recognition Application Using Yolov5 Architecture. Proceedings of the 2021 International Russian Automation Conference (RusAutoCon), Sochi, Russia.","DOI":"10.1109\/RusAutoCon52004.2021.9537355"},{"key":"ref_32","unstructured":"GitHub (2022, December 01). Meituan. YOLOv6. 27 August 2022. Available online: https:\/\/github.com\/meituan\/YOLOv6."},{"key":"ref_33","unstructured":"Wang, C.-Y., Bochkovskiy, A., and Liao, H.-Y.M. (2022). YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. arXiv, Available online: https:\/\/arxiv.org\/abs\/2207.02696."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1007\/s42979-021-00815-1","article-title":"Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions","volume":"2","author":"Sarker","year":"2021","journal-title":"SN Comput. Sci."},{"key":"ref_35","unstructured":"Strutz, T. (2021). The Distance Transform and Its Computation. arXiv."},{"key":"ref_36","unstructured":"(2022, December 01). Colaboratory. Available online: https:\/\/colab.research.google.com\/notebooks\/intro.ipynb."},{"key":"ref_37","first-page":"1073","article-title":"Hybrid features for object detection in RGB-D scenes","volume":"23","author":"Awwad","year":"2021","journal-title":"Indones. J. Electr. Eng. Comput. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Papadeas, I., Tsochatzidis, L., Amanatiadis, A., and Pratikakis, I. (2021). Real-Time Semantic Image Segmentation with Deep Learning for Autonomous Driving: A Survey. Appl. Sci., 11.","DOI":"10.3390\/app11198802"},{"key":"ref_39","unstructured":"Tk\u00e1\u010dov\u00e1, M., and Foffov\u00e1, P. (2011, January 27\u201330). A Reference for Human Eye Surface Temperature Measurements in Diagnostic Process of Ophthalmologic Diseases. Proceedings of the Measurement 2011 8th International Conference, Smolenice, Slovakia. Available online: https:\/\/www.measurement.sk\/M2011\/doc\/proceedings\/406_Tkacova-2.pdf."},{"key":"ref_40","unstructured":"Saint Luke\u2019s Health System (2022, December 01). Understanding Nasal Anatomy: Inside View. Available online: https:\/\/www.saintlukeskc.org\/health-library\/understanding-nasal-anatomy-inside-view."},{"key":"ref_41","unstructured":"MedlinePlus (2022, December 01). Aging Changes in the Face: MedlinePlus Medical Encyclopedia, Available online: https:\/\/medlineplus.gov\/ency\/article\/004004.htm."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/1851\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:26:43Z","timestamp":1760120803000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/1851"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,7]]},"references-count":41,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["s23041851"],"URL":"https:\/\/doi.org\/10.3390\/s23041851","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2023,2,7]]}}}