{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T15:41:30Z","timestamp":1760370090882,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T00:00:00Z","timestamp":1732752000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia (FCT, Portugal)","award":["UIDB\/00013\/2020","UIDB\/04650\/2020","UIDB\/00324\/2020","POCI-01-0247-FEDER-037902"],"award-info":[{"award-number":["UIDB\/00013\/2020","UIDB\/04650\/2020","UIDB\/00324\/2020","POCI-01-0247-FEDER-037902"]}]},{"name":"European Structural and Investment Funds in the FEDER component","award":["UIDB\/00013\/2020","UIDB\/04650\/2020","UIDB\/00324\/2020","POCI-01-0247-FEDER-037902"],"award-info":[{"award-number":["UIDB\/00013\/2020","UIDB\/04650\/2020","UIDB\/00324\/2020","POCI-01-0247-FEDER-037902"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>We study the problem of classification of various real-world objects using as input a database (DB) of laboratory polarimetric measures (Mueller matrix elements\u2014MMEs). It can work as a complementary technology of surroundings\u2019 imaging that can be used, in particular, in autonomous driving. To this end, we look for an algorithm using less input parameters without great loss of the quality of classification. We start by analyzing the data in order to understand the attributes that are more important for associating the objects with one of several predefined classes. Different sets of attributes are studied using an artificial neural network (ANN), which is optimized in terms of the number of hidden layers and the activation function. After that, an improved machine learning (ML) architecture is built using the K-nearest neighbors (KNN) classifier on each cluster generated by applying the pre-trained ANN to the training set. This article focuses on the situation wherein one may not be able to measure all MMEs or it would be too expensive or challenging to implement when the measurement time is crucial. The results obtained for a reduced set of attributes using different ML architectures are very good, especially for the proposed combined ANN-KNN approach (wherein the ANN acts as a predictor and KNN as a corrector), which can help to avoid measuring all MMEs.<\/jats:p>","DOI":"10.3390\/app142311059","type":"journal-article","created":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T03:21:23Z","timestamp":1732764083000},"page":"11059","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Classification of Real-World Objects Using Supervised ML-Assisted Polarimetry: Cost\/Benefit Analysis"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7056-0092","authenticated-orcid":false,"given":"Rui M. S.","family":"Pereira","sequence":"first","affiliation":[{"name":"Department of Mathematics and Centre of Mathematics, University of Minho, 4710-057 Braga, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0693-4712","authenticated-orcid":false,"given":"Filipe","family":"Oliveira","sequence":"additional","affiliation":[{"name":"Centro de F\u00edsica das Universidades do Minho e do Porto, Laborat\u00f3rio de F\u00edsica para Materiais e Tecnologias Emergentes (LaPMET), Universidade do Minho, 4710-057 Braga, Portugal"}]},{"given":"Nazar","family":"Romanyshyn","sequence":"additional","affiliation":[{"name":"Centro de F\u00edsica das Universidades do Minho e do Porto, Laborat\u00f3rio de F\u00edsica para Materiais e Tecnologias Emergentes (LaPMET), Universidade do Minho, 4710-057 Braga, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3693-8335","authenticated-orcid":false,"given":"Irene","family":"Estevez","sequence":"additional","affiliation":[{"name":"Centro de F\u00edsica das Universidades do Minho e do Porto, Laborat\u00f3rio de F\u00edsica para Materiais e Tecnologias Emergentes (LaPMET), Universidade do Minho, 4710-057 Braga, Portugal"},{"name":"Grup d\u2019\u00d2ptica, Physics Department, Universitat Aut\u00f2noma de Barcelona, 08193 Bellaterra, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7421-6902","authenticated-orcid":false,"given":"Joel","family":"Borges","sequence":"additional","affiliation":[{"name":"Centro de F\u00edsica das Universidades do Minho e do Porto, Laborat\u00f3rio de F\u00edsica para Materiais e Tecnologias Emergentes (LaPMET), Universidade do Minho, 4710-057 Braga, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2295-5118","authenticated-orcid":false,"given":"Stephane","family":"Clain","sequence":"additional","affiliation":[{"name":"Centre of Mathematics (CMUC), Coimbra University, 3004-531 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2930-9434","authenticated-orcid":false,"given":"Mikhail I.","family":"Vasilevskiy","sequence":"additional","affiliation":[{"name":"Centro de F\u00edsica das Universidades do Minho e do Porto, Laborat\u00f3rio de F\u00edsica para Materiais e Tecnologias Emergentes (LaPMET), Universidade do Minho, 4710-057 Braga, Portugal"},{"name":"International Iberian Nanotechnology Laboratory, Av. Mestre Jos\u00e9 Veiga, 4715-330 Braga, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s11263-019-01247-4","article-title":"Deep Learning for Generic Object Detection: A Survey","volume":"128","author":"Liu","year":"2020","journal-title":"Int. J. Comput. Vis."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"103812","DOI":"10.1016\/j.dsp.2022.103812","article-title":"A comprehensive review of object detection with deep learning","volume":"132","author":"Kaur","year":"2023","journal-title":"Digit. Signal Process."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Galv\u00e3o, L., Abbod, M., Kalganova, T., Palade, V., and Huda, N. (2021). Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems\u2014A Review. 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