{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T16:25:45Z","timestamp":1774369545664,"version":"3.50.1"},"reference-count":14,"publisher":"China Science Publishing & Media Ltd.","issue":"4","content-domain":{"domain":["www.mitpressjournals.org"],"crossmark-restriction":true},"short-container-title":["Data Intelligence"],"published-print":{"date-parts":[[2020,10]]},"abstract":"<jats:p> In this paper, we report upon our recent work aimed at improving and adapting machine learning algorithms to automatically classify nanoscience images acquired by the Scanning Electron Microscope (SEM). This is done by coupling supervised and unsupervised learning approaches. We first investigate supervised learning on a ten-category data set of images and compare the performance of the different models in terms of training accuracy. Then, we reduce the dimensionality of the features through autoencoders to perform unsupervised learning on a subset of images in a selected range of scales (from 1 \u03bcm to 2 \u03bcm). Finally, we compare different clustering methods to uncover intrinsic structures in the images. <\/jats:p>","DOI":"10.1162\/dint_a_00062","type":"journal-article","created":{"date-parts":[[2020,9,3]],"date-time":"2020-09-03T15:37:58Z","timestamp":1599147478000},"page":"513-528","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":25,"title":["Deep Learning, Feature Learning, and Clustering Analysis for SEM                     Image Classification"],"prefix":"10.3724","volume":"2","author":[{"given":"Rossella","family":"Aversa","sequence":"first","affiliation":[{"name":"National Research Council-Istituto Officina dei Materiali (CNR-IOM), 34136                         Trieste, Italy."},{"name":"KIT-Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344                         Eggenstein-Leopoldshafen, Germany."}]},{"given":"Piero","family":"Coronica","sequence":"additional","affiliation":[{"name":"National Research Council-Istituto Officina dei Materiali (CNR-IOM), 34136                         Trieste, Italy."},{"name":"Research Software Engineering, University of Cambridge, Cambridge CB3 0FA,                         UK."}]},{"given":"Cristiano","family":"De Nobili","sequence":"additional","affiliation":[{"name":"National Research Council-Istituto Officina dei Materiali (CNR-IOM), 34136                         Trieste, Italy."},{"name":"Freelance at ."}]},{"given":"Stefano","family":"Cozzini","sequence":"additional","affiliation":[{"name":"National Research Council-Istituto Officina dei Materiali (CNR-IOM), 34136                         Trieste, Italy."},{"name":"Area Science Park, Padriciano 99, 34149 Trieste, Italy."}]}],"member":"2026","reference":[{"key":"ref2","first-page":"465","volume-title":"Artificial Neural Networks\u2014Application","author":"Amani A.","year":"2011"},{"issue":"40","key":"ref3","doi-asserted-by":"crossref","DOI":"10.1088\/0957-4484\/20\/40\/405708","volume":"20","author":"Nikiforov M.P.","year":"2009","journal-title":"Nanotechnology"},{"issue":"35","key":"ref4","volume":"18","author":"Al-Khedher M.A.","year":"2007","journal-title":"Nanotechnology"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.18"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2018.172"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-13565-z"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2025923"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.165"},{"key":"ref28","first-page":"66","volume":"10","author":"van Der Maaten L.","year":"2009","journal-title":"Journal of Machining Learning Research"},{"key":"ref29","volume-title":"Hands-on machine learning with Scikit-Learn and Tensor-Flow","author":"G\u00e9ron A.","year":"2017"},{"issue":"1","key":"ref30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-016-0028-x","volume":"7","author":"Facco E.","year":"2017","journal-title":"Scientific Report"},{"issue":"6191","key":"ref31","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"Rodriguez A.","year":"2014","journal-title":"Science"},{"issue":"9","key":"ref32","doi-asserted-by":"crossref","first-page":"P09008","DOI":"10.1088\/1742-5468\/2005\/09\/P09008","volume":"2005","author":"Danon L.","year":"2005","journal-title":"Journal of Statistical Mechanics: Theory and Experiment"}],"container-title":["Data Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/dint_a_00062","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T07:43:22Z","timestamp":1741938202000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.sciengine.com\/doi\/10.1162\/dint_a_00062"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10]]},"references-count":14,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,10]]}},"alternative-id":["10.1162\/dint_a_00062"],"URL":"https:\/\/doi.org\/10.1162\/dint_a_00062","relation":{},"ISSN":["2641-435X"],"issn-type":[{"value":"2641-435X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10]]},"assertion":[{"value":"2020-10-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}