no code implementations • 22 Jun 2023 • Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
Cascade systems comprise a two-model sequence, with a lightweight model processing all samples and a heavier, higher-accuracy model conditionally refining harder samples to improve accuracy.
no code implementations • 20 Jun 2023 • Ioannis Panopoulos, Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
Deep learning (DL) is characterised by its dynamic nature, with new deep neural network (DNN) architectures and approaches emerging every few years, driving the field's advancement.
no code implementations • 21 Jun 2021 • Stylianos I. Venieris, Ioannis Panopoulos, Ilias Leontiadis, Iakovos S. Venieris
Collectively, these results highlight the critical need for further exploration as to how the various cross-stack solutions can be best combined in order to bring the latest advances in deep learning close to users, in a robust and efficient manner.
no code implementations • 8 Jun 2021 • Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris
Radical progress in the field of deep learning (DL) has led to unprecedented accuracy in diverse inference tasks.
no code implementations • 1 Nov 2018 • Panagiotis Kasnesis, Charalampos Z. Patrikakis, Iakovos S. Venieris
Human Activity Recognition (HAR) based on motion sensors has drawn a lot of attention over the last few years, since perceiving the human status enables context-aware applications to adapt their services on users' needs.