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Designed for training neural networks focused on developing Fiber Optic Specklegram Sensors (FSSs), these experimental data enable the detection of changes in speckle patterns corresponding to applied temperature variations. The dataset includes 24,528 images captured over a temperature range from 25 \u00b0C to 200 \u00b0C, with incremental steps of approximately 0.175 \u00b0C. Key acquisition parameters include a wavelength of 633 nm, a sensing zone length of 20 mm, and a multimode fiber with a core diameter of 62.5 \u03bcm. This dataset supports developing and validating temperature-sensing models using fiber optic technology and can facilitate benchmarking against other experimental or synthetic datasets. Finally, an implementation is presented for utilizing the dataset in a deep learning interrogation scheme.<\/jats:p>","DOI":"10.3390\/data10040044","type":"journal-article","created":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T13:39:53Z","timestamp":1742996393000},"page":"44","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Experimental Dataset for Fiber Optic Specklegram Sensing Under Thermal Conditions and Use in a Deep Learning Interrogation Scheme"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4267-042X","authenticated-orcid":false,"given":"Francisco J.","family":"V\u00e9lez","sequence":"first","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Cooperativa de Colombia, Medell\u00edn 050012, Colombia"},{"name":"School of Applied Sciences and Engineering, EAFIT University, Medell\u00edn 050022, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan D.","family":"Arango","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnol\u00f3gico Metropolitano, Medell\u00edn 050013, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7880-5883","authenticated-orcid":false,"given":"V\u00edctor H.","family":"Aristiz\u00e1bal","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Cooperativa de Colombia, Medell\u00edn 050012, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1007-5028","authenticated-orcid":false,"given":"Carlos","family":"Trujillo","sequence":"additional","affiliation":[{"name":"School of Applied Sciences and Engineering, EAFIT University, Medell\u00edn 050022, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5536-7147","authenticated-orcid":false,"given":"Jorge A.","family":"Herrera-Ram\u00edrez","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnol\u00f3gico Metropolitano, Medell\u00edn 050013, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yu, F.T.S. (2018). Fiber Specklegram Sensors. Fiber Opt. Sens., 201\u2013252.","DOI":"10.1201\/9781420053661-6"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1109\/JSEN.2019.2944906","article-title":"Optical Fiber Specklegram Sensors for Mechanical Measurements: A Review","volume":"20","author":"Frizera","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"106424","DOI":"10.1016\/j.optlastec.2020.106424","article-title":"Bending Recognition Based on the Analysis of Fiber Specklegrams Using Deep Learning","volume":"131","author":"Liu","year":"2020","journal-title":"Opt. Laser Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2055","DOI":"10.1109\/JSEN.2017.2658683","article-title":"A Review of Fiber-Optic Modal Modulated Sensors: Specklegram and Modal Power Distribution Sensing","volume":"17","author":"Efendioglu","year":"2017","journal-title":"IEEE Sens. 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Fiber Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"8966","DOI":"10.1109\/JLT.2024.3439347","article-title":"A Novel Structure with Ultra Short Multimode Fiber for Fiber Specklegram Sensor and Its Application in Multi-Bending Sensing. Proof and Concept","volume":"42","author":"Li","year":"2024","journal-title":"J. Light. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1364\/AO.56.001585","article-title":"Optical Fiber Specklegram Sensor Analysis by Speckle Pattern Division","volume":"56","author":"Fujiwara","year":"2017","journal-title":"Appl. Opt."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Gubarev, F., Li, L., Klenovskii, M., and Glotov, A. (2016, January 12\u201314). Speckle Pattern Processing by Digital Image Correlation. Proceedings of the MATEC Web of Conferences, Tomsk, Russia.","DOI":"10.1051\/matecconf\/20164804003"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"689","DOI":"10.18287\/2412-6179-CO-1467","article-title":"Comparative Performance Evaluation of Classical Methods and a Deep Learning Approach for Temperature Prediction in Fiber Optic Specklegram Sensors","volume":"48","author":"Arango","year":"2024","journal-title":"Comput. Opt."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.1109\/LPT.2023.3313584","article-title":"Deep Learning for Temperature Sensing with Microstructure Fiber in Noise Perturbation Environment","volume":"35","author":"Gao","year":"2023","journal-title":"IEEE Photonics Technol. 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Proceedings of the Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP), Boston, MA, USA. paper ITh2E.3.","DOI":"10.1364\/ISA.2023.ITh2E.3"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"534","DOI":"10.18287\/2412-6179-CO-852","article-title":"Numerical Study Using Finite Element Method for the Thermal Response of Fiber Specklegram Sensors with Changes in the Length of the Sensing Zone","volume":"45","author":"Arango","year":"2021","journal-title":"Comput. Opt."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Chitrapu, P., and Kalluri, H.K. (2024, January 24\u201325). MobileNet-Powered Deep Learning for Efficient Face Classification. 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