1 citations · 1 across the 4 of their papers we have counts for
4 papers
Learn&Drop: Fast Learning of CNNs based on Layer Dropping
Giorgio Cruciata, Luca Cruciata, Liliana Lo Presti +2
This paper proposes a new method to improve the training efficiency of deep convolutional neural networks. During training, the method evaluates scores to measure how much each lay…
Deep activity propagation via weight initialization in spiking neural networks
Aurora Micheli, Olaf Booij, Jan van Gemert +1
Spiking Neural Networks (SNNs) and neuromorphic computing offer bio-inspired advantages such as sparsity and ultra-low power consumption, providing a promising alternative to conve…
VIPriors 3: Visual Inductive Priors for Data-Efficient Deep Learning Challenges
Robert-Jan Bruintjes, Attila Lengyel, Marcos Baptista Rios +4
The third edition of the "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" workshop featured four data-impaired challenges, focusing on addressing the limitation…
Deep vanishing point detection: Geometric priors make dataset variations vanish
Yancong Lin, Ruben Wiersma, Silvia L. Pintea +3
Deep learning has improved vanishing point detection in images. Yet, deep networks require expensive annotated datasets trained on costly hardware and do not generalize to even sli…