Anas Skalli, X. Porte, N. Haghighi, S. Reitzenstein, J. Lott, D. Brunner
{"title":"Computational metrics of an injection-locked large area semiconductor laser for neural network computing (Conference Presentation)","authors":"Anas Skalli, X. Porte, N. Haghighi, S. Reitzenstein, J. Lott, D. Brunner","doi":"10.1117/12.2633381","DOIUrl":"https://doi.org/10.1117/12.2633381","url":null,"abstract":"","PeriodicalId":179507,"journal":{"name":"Emerging Topics in Artificial Intelligence (ETAI) 2022","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128591732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Canal-Garcia, D. Veréb, M. Mijalkov, G. Volpe, J. Pereira
{"title":"Multilayer brain connectivity analysis in Alzheimer’s disease using functional MRI data (Conference Presentation)","authors":"A. Canal-Garcia, D. Veréb, M. Mijalkov, G. Volpe, J. Pereira","doi":"10.1117/12.2632379","DOIUrl":"https://doi.org/10.1117/12.2632379","url":null,"abstract":"","PeriodicalId":179507,"journal":{"name":"Emerging Topics in Artificial Intelligence (ETAI) 2022","volume":"281 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131695575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Midtvedt, Erik Olsén, Benjamin Midtvedt, E. K. Esbjörner, Fredrik Skärberg, Berenice Garcia, C. Adiels, F. Höök, G. Volpe
{"title":"Label-free characterization of biological matter across scales (Conference Presentation)","authors":"Daniel Midtvedt, Erik Olsén, Benjamin Midtvedt, E. K. Esbjörner, Fredrik Skärberg, Berenice Garcia, C. Adiels, F. Höök, G. Volpe","doi":"10.1117/12.2633978","DOIUrl":"https://doi.org/10.1117/12.2633978","url":null,"abstract":"","PeriodicalId":179507,"journal":{"name":"Emerging Topics in Artificial Intelligence (ETAI) 2022","volume":"10 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124291778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Krzysztof Tyszka, M. Furman, R. Mirek, M. Król, A. Opala, B. Seredyński, J. Suffczyński, W. Pacuski, M. Matuszewski, J. Szczytko, B. Piętka
{"title":"Optical spike processing with exciton-polariton microcavities (Conference Presentation)","authors":"Krzysztof Tyszka, M. Furman, R. Mirek, M. Król, A. Opala, B. Seredyński, J. Suffczyński, W. Pacuski, M. Matuszewski, J. Szczytko, B. Piętka","doi":"10.1117/12.2631985","DOIUrl":"https://doi.org/10.1117/12.2631985","url":null,"abstract":"","PeriodicalId":179507,"journal":{"name":"Emerging Topics in Artificial Intelligence (ETAI) 2022","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132829487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Machine learning for scanning probe and electron microscopy for materials discovery (Conference Presentation)","authors":"S. Kalinin, Yongtao Liu","doi":"10.1117/12.2635229","DOIUrl":"https://doi.org/10.1117/12.2635229","url":null,"abstract":"","PeriodicalId":179507,"journal":{"name":"Emerging Topics in Artificial Intelligence (ETAI) 2022","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133109395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin Midtvedt, Jesús D. Pineda Castro, Fredrik Skärberg, Erik Olsén, Harshith Bachimanchi, Emelie V. Wesén, E. K. Esbjörner, Erik Selander, F. Höök, Daniel Midtvedt, Giovanni Volpe
{"title":"Single-shot self-supervised particle tracking (Conference Presentation)","authors":"Benjamin Midtvedt, Jesús D. Pineda Castro, Fredrik Skärberg, Erik Olsén, Harshith Bachimanchi, Emelie V. Wesén, E. K. Esbjörner, Erik Selander, F. Höök, Daniel Midtvedt, Giovanni Volpe","doi":"10.1117/12.2633355","DOIUrl":"https://doi.org/10.1117/12.2633355","url":null,"abstract":"Particle tracking is a fundamental task in digital microscopy. Recently, machine-learning approaches have made great strides in overcoming the limitations of more classical approaches. The training of state-of-the-art machine-learning methods almost universally relies on either vast amounts of labeled experimental data or the ability to numerically simulate realistic datasets. However, the data produced by experiments are often challenging to label and cannot be easily reproduced numerically. Here, we propose a novel deep-learning method, named LodeSTAR (Low-shot deep Symmetric Tracking And Regression), that learns to tracks objects with sub-pixel accuracy from a single unlabeled experimental image. This is made possible by exploiting the inherent roto-translational symmetries of the data. We demonstrate that LodeSTAR outperforms traditional methods in terms of accuracy. Furthermore, we analyze challenging experimental data containing densely packed cells or noisy backgrounds. We also exploit additional symmetries to extend the measurable particle properties to the particle's vertical position by propagating the signal in Fourier space and its polarizability by scaling the signal strength. Thanks to the ability to train deep-learning models with a single unlabeled image, LodeSTAR can accelerate the development of high-quality microscopic analysis pipelines for engineering, biology, and medicine.","PeriodicalId":179507,"journal":{"name":"Emerging Topics in Artificial Intelligence (ETAI) 2022","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115100071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}