{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T01:25:57Z","timestamp":1769045157896,"version":"3.49.0"},"reference-count":73,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T00:00:00Z","timestamp":1691712000000},"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>Regular inspections during construction work ensure that the completed work aligns with the plans and specifications and that it is within the planned time and budget. This requires frequent physical site observations to independently measure and verify the completion percentage of the construction progress performed over periods of time. The current computer vision techniques for measuring as-built elements predominantly employ three-dimensional laser scanning or three-dimensional photogrammetry modeling to ascertain the geometric properties of as-built elements on construction sites. Both techniques require data acquisition from several positions and angles to generate sufficient information about the element\u2019s coordinates, making the deployment of these techniques on dynamic construction project sites challenging. This paper proposes a pipeline for automating the measurement of as-built components using artificial intelligence and computer vision techniques. The pipeline requires a single image obtained with a stereo camera system to measure the sizes of selected objects or as-built components. The results in this work were demonstrated by measuring the sizes of concrete walls and columns. The novelty of this work is attributed to the use of a single image and a single target for developing a fully automated computer vision-based method for measuring any given object. The proposed solution is suitable for use in measuring the sizes of as-built components in built assets. It has the potential to be further developed and integrated with building information modelling applications for use on construction projects for progress monitoring.<\/jats:p>","DOI":"10.3390\/s23167110","type":"journal-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T12:10:23Z","timestamp":1691755823000},"page":"7110","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Towards Automated Measurement of As-Built Components Using Computer Vision"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6475-5638","authenticated-orcid":false,"given":"Husein","family":"Perez","sequence":"first","affiliation":[{"name":"Oxford Institute for Sustainable Development, School of the Built Environment, Oxford Brookes University, Oxford OX3 0BP, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1950-8387","authenticated-orcid":false,"given":"Joseph H. M.","family":"Tah","sequence":"additional","affiliation":[{"name":"Oxford Institute for Sustainable Development, School of the Built Environment, Oxford Brookes University, Oxford OX3 0BP, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1061\/(ASCE)0887-3801(1995)9:1(9)","article-title":"Simulation of automated data collection in buildings","volume":"9","author":"Davidson","year":"1995","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.autcon.2006.03.003","article-title":"Research in automated measurement of project performance indicators","volume":"16","author":"Navon","year":"2007","journal-title":"Autom. Constr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.autcon.2006.07.001","article-title":"Synchronization-based model for improving on-site data collection performance","volume":"16","author":"Tsai","year":"2007","journal-title":"Autom. Constr."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Saidi, K.S., Lytle, A.M., and Stone, W.C. (2003, January 21\u201324). Report of the NIST workshop on data exchange standards at the construction job site. Proceedings of the 20th International Symposium on Automation and Robotics in Construction (ISARC), Eindhoven, The Netherlands.","DOI":"10.22260\/ISARC2003\/0095"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1061\/(ASCE)CO.1943-7862.0000055","article-title":"Cost and Schedule Monitoring of Industrial Building Projects: Case Study","volume":"135","author":"Briccarello","year":"2009","journal-title":"J. Constr. Eng. Manag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/j.autcon.2006.08.001","article-title":"Assessing research issues in automated project performance control (APPC)","volume":"16","author":"Navon","year":"2007","journal-title":"Autom. Constr."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Manfren, M., Tagliabue, L.C., Re Cecconi, F., and Ricci, M. (2022). Long-term techno-economic performance monitoring to promote built environment decarbonisation and digital transformation\u2014A case study. Sustainability, 14.","DOI":"10.3390\/su14020644"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.autcon.2016.06.016","article-title":"Data acquisition technologies for construction progress tracking","volume":"70","author":"Omar","year":"2016","journal-title":"Autom. Constr."},{"key":"ref_9","unstructured":"Bradski, G., and Kaehler, A. (2008). Learning OpenCV: Computer Vision with the OpenCV Library, O\u2019Reilly Media, Inc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1061\/(ASCE)CO.1943-7862.0000164","article-title":"Benefits and Barriers of Construction Project Monitoring Using High-Resolution Automated Cameras","volume":"136","author":"Bohn","year":"2010","journal-title":"J. Constr. Eng. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1099","DOI":"10.1061\/(ASCE)CO.1943-7862.0000371","article-title":"Integrated Sequential As-Built and As-Planned Representation with D4AR Tools in Support of Decision-Making Tasks in the AEC\/FM Industry","volume":"137","author":"Savarese","year":"2011","journal-title":"J. Constr. Eng. Manag."},{"key":"ref_12","first-page":"4","article-title":"Tracking the built status of MEP works: Assessing the value of a Scan-vs-BIM system","volume":"28","author":"Guillemet","year":"2014","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.autcon.2008.09.004","article-title":"Automating progress measurement of construction projects","volume":"18","author":"Zhang","year":"2009","journal-title":"Autom. Constr."},{"key":"ref_14","unstructured":"Fisher, R.B., Breckon, T.P., Dawson-Howe, K., Fitzgibbon, A., Robertson, C., Trucco, E., and Williams, C.K.I. (2013). Dictionary of Computer Vision and Image Processing, John Wiley & Sons."},{"key":"ref_15","unstructured":"Guinchard, M., Angeletti, M., Boyer, F., Catinaccio, A., Gargiulo, C., Lacny, L., Laudi, E., and Scislo, L. (May, January 29). Experimental modal analysis of lightweight structures used in particle detectors: Optical non-contact method. Proceedings of the 9th International Particle Accelerator Conference, IPAC18, Vancouver, BC, Canada."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1080\/01446193.2011.554846","article-title":"Progress monitoring of construction projects using pattern recognition techniques","volume":"29","author":"Elazouni","year":"2011","journal-title":"Constr. Manag. Econ."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Lukins, T.C., and Trucco, E. (2007, January 10\u201313). Towards automated visual assessment of progress in construction projects. Proceedings of the British Machine Vision Conference, Warwick, UK.","DOI":"10.5244\/C.21.18"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.aei.2008.06.002","article-title":"Automated construction activity monitoring system","volume":"22","author":"Rebolj","year":"2008","journal-title":"Adv. Eng. Inform."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.autcon.2006.12.005","article-title":"Comparison of construction photograph and VR image in construction progress","volume":"17","author":"Kim","year":"2008","journal-title":"Autom. Constr."},{"key":"ref_20","unstructured":"Kopsida, M., Brilakis, I., and Vela, P.A. (2015, January 27\u201329). A review of automated construction progress monitoring and inspection methods. Proceedings of the 32nd CIB W78 Conference 2015, Eindhoven, The Netherlands."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"\u00c1lvares, J.S., and Costa, D.B. (2018, January 6\u201322). Literature review on visual construction progress monitoring using unmanned aerial vehicles. Proceedings of the 26th Annual Conference of the International Group for Lean Construction: Evolving Lean Construction Towards Mature Production Management Across Cultures and Frontiers, Chennai, India.","DOI":"10.24928\/2018\/0310"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.aei.2015.03.006","article-title":"Status quo and open challenges in vision-based sensing and tracking of temporary resources on infrastructure construction sites","volume":"29","author":"Teizer","year":"2015","journal-title":"Adv. Eng. Inform."},{"key":"ref_23","unstructured":"Borrmann, A., and Stilla, U. (2015, January 15\u201318). Automated Progress Monitoring Based on Photogrammetric Point Clouds and Precedence Relationship Graphs. Proceedings of the 32nd International Symposium on Automation and Robotics in Construction (ISARC), Oulu, Finland."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.aei.2013.11.002","article-title":"Vision-based material recognition for automated monitoring of construction progress and generating building information modeling from unordered site image collections","volume":"28","author":"Dimitrov","year":"2014","journal-title":"Adv. Eng. Inform."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"103236","DOI":"10.1016\/j.autcon.2020.103236","article-title":"Automatic pipe and elbow recognition from three-dimensional point cloud model of industrial plant piping system using convolutional neural network-based primitive classification","volume":"116","author":"Kim","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chen, J., Fang, Y., and Cho, Y.K. (2017, January 25\u201327). Unsupervised Recognition of Volumetric Structural Components from Building Point Clouds. Proceedings of the ASCE International Workshop on Computing in Civil Engineering, Seattle, DC, USA.","DOI":"10.1061\/9780784480823.005"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Riley, K.F., Hobson, M.P., and Bence, S.J. (1999). Mathematical Methods for Physics and Engineering, American Association of Physics Teachers.","DOI":"10.1119\/1.19216"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.autcon.2012.11.041","article-title":"Automated construction progress measurement using a 4D building information model and 3D data","volume":"31","author":"Kim","year":"2013","journal-title":"Autom. Constr."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1080\/01446190801918748","article-title":"Minimum performance bounds for evaluating contractors\u2019 performance during construction of highway pavement projects","volume":"26","year":"2008","journal-title":"Constr. Manag. Econ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.habitatint.2012.06.008","article-title":"Identifying the critical factors affecting schedule performance of public housing projects","volume":"38","author":"Hwang","year":"2013","journal-title":"Habitat Int."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.autcon.2011.10.003","article-title":"Automated progress tracking using 4D schedule and 3D sensing technologies","volume":"22","author":"Turkan","year":"2012","journal-title":"Autom. Constr."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Witzgall, C.J., Bernal, J., and Cheok, G. (2004). TIN techniques for data analysis and surface construction. Christoph J. Witzgall Javier Bernal Geraldine Cheok.","DOI":"10.6028\/NIST.IR.7078"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1016\/j.autcon.2006.11.002","article-title":"3D laser scanning and GPS technology for landslide earthwork volume estimation","volume":"16","author":"Du","year":"2007","journal-title":"Autom. Constr."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1061\/(ASCE)1076-0431(2004)10:3(98)","article-title":"Point-cloud-based comparison between construction schedule and as-built progress: Long-range three-dimensional laser scanner\u2019s approach","volume":"10","author":"Shih","year":"2004","journal-title":"J. Archit. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.aei.2009.08.006","article-title":"Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction","volume":"24","year":"2010","journal-title":"Adv. Eng. Inform."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1016\/j.autcon.2010.03.003","article-title":"3D structural component recognition and modeling method using color and 3D data for construction progress monitoring","volume":"19","author":"Son","year":"2010","journal-title":"Autom. Constr."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"04014025","DOI":"10.1061\/(ASCE)CP.1943-5487.0000205","article-title":"Automated progress monitoring using unordered daily construction photographs and IFC-based building information models","volume":"29","author":"Savarese","year":"2015","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"012008","DOI":"10.1088\/1757-899X\/955\/1\/012008","article-title":"Monitoring of Historical Structures using Drones","volume":"955","author":"Taj","year":"2020","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1111\/mice.12693","article-title":"Metrics and methods for evaluating model-driven reality capture plans","volume":"37","author":"Ibrahim","year":"2021","journal-title":"Comput. Civ. Infrastruct. Eng."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Wu, Y., Wang, M., Liu, X., Wang, Z., Ma, T., Xie, Y., Li, X., and Wang, X. (2021). Construction of Stretching-Bending Sequential Pattern to Recognize Work Cycles for Earthmoving Excavator from Long Video Sequences. Sensors, 21.","DOI":"10.3390\/s21103427"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Shang, Z., and Shen, Z. (2017). Real-Time 3D Reconstruction on Construction Site Using Visual SLAM and UAV. arXiv.","DOI":"10.1061\/9780784481264.030"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Shojaei, A., Moud, H.I., and Flood, I. (2018, January 2\u20134). Proof of Concept for the Use of Small Unmanned Surface Vehicle in Built Environment Management. Proceedings of the Construction Research Congress 2018: Construction Information Technology\u2014Selected Papers from the Construction Research Congress, New Orleans, LA, USA.","DOI":"10.1061\/9780784481264.012"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1108\/CI-07-2018-0059","article-title":"Imaging network design to improve the automated construction progress monitoring process","volume":"19","author":"Mahami","year":"2019","journal-title":"Constr. Innov."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s40327-017-0052-3","article-title":"Crowdsourcing BIM-guided collection of construction material library from site photologs","volume":"5","author":"Han","year":"2017","journal-title":"Vis. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Kielhauser, C., Manzano, R.R., Hoffman, J.J., and Adey, B.T. (2020). Automated Construction Progress and Quality Monitoring for Commercial Buildings with Unmanned Aerial Systems: An Application Study from Switzerland. Infrastructures, 5.","DOI":"10.3390\/infrastructures5110098"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"102879","DOI":"10.1016\/j.autcon.2019.102879","article-title":"Combining inverse photogrammetry and BIM for automated labeling of construction site images for machine learning","volume":"106","author":"Braun","year":"2019","journal-title":"Autom. Constr."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"581295","DOI":"10.3389\/fbuil.2020.581295","article-title":"Multi-Building Extraction and Alignment for As-Built Point Clouds: A Case Study With Crane Cameras","volume":"6","author":"Masood","year":"2020","journal-title":"Front. Built Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.aei.2011.08.009","article-title":"Plane-based registration of construction laser scans with 3D\/4D building models","volume":"26","year":"2012","journal-title":"Adv. Eng. Inform."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.autcon.2018.01.014","article-title":"4-Plane congruent sets for automatic registration of as-is 3D point clouds with 3D BIM models","volume":"89","author":"Bueno","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1016\/j.autcon.2006.09.003","article-title":"Digital documentation of historical buildings with 3-d modeling functionality","volume":"16","author":"Styliadis","year":"2007","journal-title":"Autom. Constr."},{"key":"ref_51","first-page":"37","article-title":"Use of photogrammetry in 3D modeling and visualization of buildings","volume":"2","author":"Shashi","year":"2007","journal-title":"ARPN J. Eng. Appl. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.autcon.2008.05.006","article-title":"Integrating 3D laser scanning and photogrammetry for progress measurement of construction work","volume":"18","author":"Moselhi","year":"2008","journal-title":"Autom. Constr."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/S0924-2716(99)00014-3","article-title":"A comparison between photogrammetry and laser scanning","volume":"54","author":"Baltsavias","year":"1999","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1016\/j.autcon.2011.04.016","article-title":"Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques","volume":"20","author":"Bohn","year":"2011","journal-title":"Autom. Constr."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"9040","DOI":"10.1364\/OE.27.009040","article-title":"Stereo-camera calibration for large-scale DIC measurements with active phase targets and planar mirrors","volume":"27","author":"Genovese","year":"2019","journal-title":"Opt. Express"},{"key":"ref_56","unstructured":"Bian, J.-W., Wu, Y.-H., Zhao, J., Liu, Y., Zhang, L., Cheng, M.-M., and Reid, I. (2019). An evaluation of feature matchers for fundamental matrix estimation. arXiv."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"107391","DOI":"10.1016\/j.measurement.2019.107391","article-title":"Underwater image matching with efficient refractive-geometry estimation for measurement in glass-flume experiments","volume":"152","author":"Sun","year":"2020","journal-title":"Measurement"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1109\/34.888718","article-title":"A Flexible New Technique for Camera Calibration","volume":"22","author":"Zhang","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"103","DOI":"10.14358\/PERS.81.2.103","article-title":"Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry","volume":"81","author":"Karara","year":"2015","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_60","unstructured":"Burger, W. (2016). Zhang\u2019s camera calibration algorithm: In-depth tutorial and implementation. HGB16-05, 1\u20136."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Barone, F., Marrazzo, M., and Oton, C.J. (2020). Camera Calibration with Weighted Direct Linear Transformation and Anisotropic Uncertainties of Image Control Points. Sensors, 20.","DOI":"10.3390\/s20041175"},{"key":"ref_62","unstructured":"Abedin-Nasab, M.H. (2020). Handbook of Robotic And image-Guided Surgery, Elsevier."},{"key":"ref_63","unstructured":"Kang, S.B., Webb, J., and Zitnick, C. (1999). An Active Multibaseline Stereo System With Real-Time Image Acquisition, Carnegie-Mellon University. Department of Computer Science."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1023\/A:1008115206617","article-title":"Theory and Practice of Projective Rectification","volume":"35","author":"Hartley","year":"1999","journal-title":"Int. J. Comput. Vis."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Lafiosca, P., and Ceccaroni, M. (2022). Rectifying homographies for stereo vision: Analytical solution for minimal distortion. arXiv.","DOI":"10.1007\/978-3-031-10464-0_33"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1612","DOI":"10.1007\/s11431-020-1582-8","article-title":"Monocular depth estimation based on deep learning: An overview","volume":"63","author":"Zhao","year":"2020","journal-title":"Sci. China Technol. Sci."},{"key":"ref_67","unstructured":"Alhashim, I., and Wonka, P. (2018). High quality monocular depth estimation via transfer learning. arXiv."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Godard, C., Mac Aodha, O., and Brostow, G.J. (2017, January 21\u201326). Unsupervised monocular depth estimation with left-right consistency. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.699"},{"key":"ref_69","first-page":"8001","article-title":"Depth prediction without the sensors: Leveraging structure for unsupervised learning from monocular videos","volume":"33","author":"Casser","year":"2019","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_70","unstructured":"Eigen, D., Puhrsch, C., and Fergus, R. (2014). Depth map prediction from a single image using a multi-scale deep network. Adv. Neural Inf. Process. Syst."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Lee, J.-H., and Kim, C.-S. (2019, January 15\u201320). Monocular depth estimation using relative depth maps. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00996"},{"key":"ref_72","unstructured":"Girshick, R., Radosavovic, I., Gkioxari, G., Doll\u00e1r, P., and He, K. (2023, July 27). Detectron. Available online: https:\/\/github.com\/facebookresearch\/detectron."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s13735-017-0141-z","article-title":"A review of semantic segmentation using deep neural networks","volume":"7","author":"Guo","year":"2018","journal-title":"Int. J. Multimed. Inf. Retr."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/16\/7110\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:31:23Z","timestamp":1760128283000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/16\/7110"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,11]]},"references-count":73,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2023,8]]}},"alternative-id":["s23167110"],"URL":"https:\/\/doi.org\/10.3390\/s23167110","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,11]]}}}