{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T21:15:47Z","timestamp":1762809347081,"version":"3.28.0"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,17]]},"DOI":"10.1109\/iecon49645.2022.9968911","type":"proceedings-article","created":{"date-parts":[[2022,12,9]],"date-time":"2022-12-09T13:45:34Z","timestamp":1670593534000},"page":"1-6","source":"Crossref","is-referenced-by-count":4,"title":["Data-Centric Model Development to Improve the CNN Classification of Defect Density SEM Images"],"prefix":"10.1109","author":[{"given":"Corinna","family":"Kofler","sequence":"first","affiliation":[{"name":"KAI GmbH,Data Science,Villach,Austria"}]},{"given":"Claudia Anna","family":"Dohr","sequence":"additional","affiliation":[{"name":"Infineon Technologies Austria AG,Defect Density,Villach,Austria"}]},{"given":"Judith","family":"Dohr","sequence":"additional","affiliation":[{"name":"Infineon Technologies Austria AG,Defect Density,Villach,Austria"}]},{"given":"Anja","family":"Zernig","sequence":"additional","affiliation":[{"name":"KAI GmbH,Data Science,Villach,Austria"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0197-0"},{"key":"ref11","article-title":"Optimizing a machine learning pipeline for SEM image classification","author":"fedel","year":"2021","journal-title":"Master&#x2019;s thesis"},{"article-title":"The Python language reference","year":"2010","author":"van rossum","key":"ref12"},{"article-title":"TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems","year":"2015","author":"abadi","key":"ref13"},{"article-title":"Keras","year":"2015","author":"chollet","key":"ref14"},{"key":"ref15","first-page":"6105","article-title":"EfficientNet: Rethinking Model Scaling for Con-volutional Neural Networks","volume":"97","author":"tan","year":"0"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2020.105652"},{"article-title":"NN-SVG: Publication-ready nn-architecture schematics","year":"2020","author":"lenail","key":"ref17"},{"journal-title":"A data-centric approach for training deep neural networks with less data","year":"2021","author":"motamedi","key":"ref4"},{"key":"ref3","first-page":"1","article-title":"Convolutional Neural Network in Com-puter Vision","author":"aishwarya","year":"2021","journal-title":"Applied Learning Algorithms for Intelligent IoT"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-018-0151-6"},{"journal-title":"Data-Centric AI Requires Rethinking Data Notion","year":"2021","author":"hajij","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-27868-9_88"},{"key":"ref7","article-title":"Classification with class imbalance problem: A Review","volume":"7","author":"ali","year":"2015","journal-title":"Int J Advance Soft Comput Appl"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ASMC.1997.630747"},{"year":"0","key":"ref1","article-title":"Intelligent reliability 4.0"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/MSR52588.2021.00048"}],"event":{"name":"IECON 2022 \u2013 48th Annual Conference of the IEEE Industrial Electronics Society","start":{"date-parts":[[2022,10,17]]},"location":"Brussels, Belgium","end":{"date-parts":[[2022,10,20]]}},"container-title":["IECON 2022 \u2013 48th Annual Conference of the IEEE Industrial Electronics Society"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9968313\/9968303\/09968911.pdf?arnumber=9968911","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T14:40:37Z","timestamp":1672065637000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9968911\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,17]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/iecon49645.2022.9968911","relation":{},"subject":[],"published":{"date-parts":[[2022,10,17]]}}}