5 citations · 5 across the 1 of their papers we have counts for
6 papers
Receptive Field Size Optimization with Continuous Time Pooling
Dóra Babicz, Soma Kontár, Márk Pető +3
The pooling operation is a cornerstone element of convolutional neural networks. These elements generate receptive fields for neurons, in which local perturbations should have mini…
Filtered Batch Normalization
Andras Horvath, Jalal Al-afandi
It is a common assumption that the activation of different layers in neural networks follow Gaussian distribution. This distribution can be transformed using normalization techniqu…
MimosaNet: An Unrobust Neural Network Preventing Model Stealing
Kálmán Szentannai, Jalal Al-Afandi, András Horváth
Deep Neural Networks are robust to minor perturbations of the learned network parameters and their minor modifications do not change the overall network response significantly. Thi…
Application-level Studies of Cellular Neural Network-based Hardware Accelerators
Qiuwen Lou, Indranil Palit, Tang Li +3
As cost and performance benefits associated with Moore's Law scaling slow, researchers are studying alternative architectures (e.g., based on analog and/or spiking circuits) and/or…
Domain Partitioning Network
Botos Csaba, Adnane Boukhayma, Viveka Kulharia +2
Standard adversarial training involves two agents, namely a generator and a discriminator, playing a mini-max game. However, even if the players converge to an equilibrium, the gen…
A mixed signal architecture for convolutional neural networks
Qiuwen Lou, Chenyun Pan, John McGuiness +4
Deep neural network (DNN) accelerators with improved energy and delay are desirable for meeting the requirements of hardware targeted for IoT and edge computing systems. Convolutio…