20.500.12556/RUL-155349 Deep learning for compressive sensing a ubiquitous systems perspective Compressive sensing (CS) is a mathematically elegant tool for reducing the sensor sampling rate, potentially bringing context-awareness to a wider range of devices. Nevertheless, practical issues with the sampling and reconstruction algorithms prevent further proliferation of CS in real world domains, especially among heterogeneous ubiquitous devices. Deep learning (DL) naturally complements CS for adapting the sampling matrix, reconstructing the signal, and learning from the compressed samples. While the CS–DL integration has received substantial research interest recently, it has not yet been thoroughly surveyed, nor has any light been shed on practical issues towards bringing the CS–DL to real world implementations in the ubiquitous computing domain. In this paper we identify main possible ways in which CS and DL can interplay, extract key ideas for making CS–DL efficient, outline major trends in the CS–DL research space, and derive guidelines for the future evolution of CS–DL within the ubiquitous computing domain. neural networks deep learning compressive sensing ubiquitous computing nevronske mreže globoko učenje kompresijsko zaznavanje vseprisotno računalništvo true false true Angleški jezik Slovenski jezik Članek v reviji 2024-03-27 10:42:25 2024-03-27 10:42:25 2024-03-28 03:55:24 0000-00-00 00:00:00 2023 0 0 Str. 3619-3658 iss. 4 Vol. 56 Apr. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.8 0269-2821 10.1007/s10462-022-10259-5 129878019 s10462-022-10259-5.pdf s10462-022-10259-5.pdf 1 91C2153E5713F1D55C26FA547304C762 ada50c308061c1898ebb6fd3cdc272e77e78af9ce63370d576af97bda3f3ff08 60900ceb-ec1f-11ee-aa14-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=182191 https://link.springer.com/article/10.1007/s10462-022-10259-5 1 525b6e58-ec1e-11ee-aa14-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=182190 Fakulteta za računalništvo in informatiko 0 0 0