28 citations · 177 across the 28 of their papers we have counts for
7 papers · 1 filter
Deep learning velocity signals allows to quantify turbulence intensity
Alessandro Corbetta, Vlado Menkovski, Roberto Benzi +1
Turbulence, the ubiquitous and chaotic state of fluid motions, is characterized by strong and statistically non-trivial fluctuations of the velocity field, over a wide range of len…
Classification of tokamak plasma confinement states with convolutional recurrent neural networks
F. Matos, V. Menkovski, F. Felici +2
During a tokamak discharge, the plasma can vary between different confinement regimes: Low (L), High (H) and, in some cases, a temporary (intermediate state), called Dithering (D).…
BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation
Iftitahu Ni'mah, Vlado Menkovski, Mykola Pechenizkiy
This study mainly investigates two common decoding problems in neural keyphrase generation: sequence length bias and beam diversity. To tackle the problems, we introduce a beam sea…
Hierarchical Annotation of Images with Two-Alternative-Forced-Choice Metric Learning
Niels Hellinga, Vlado Menkovski
Many tasks such as retrieval and recommendations can significantly benefit from structuring the data, commonly in a hierarchical way. To achieve this through annotations of high di…
Micro-expression detection in long videos using optical flow and recurrent neural networks
Michiel Verburg, Vlado Menkovski
Facial micro-expressions are subtle and involuntary expressions that can reveal concealed emotions. Micro-expressions are an invaluable source of information in application domains…
Evolutionary Construction of Convolutional Neural Networks
Marijn van Knippenberg, Vlado Menkovski, Sergio Consoli
Neuro-Evolution is a field of study that has recently gained significantly increased traction in the deep learning community. It combines deep neural networks and evolutionary algo…
StampNet: unsupervised multi-class object discovery
Joost Visser, Alessandro Corbetta, Vlado Menkovski +1
Unsupervised object discovery in images involves uncovering recurring patterns that define objects and discriminates them against the background. This is more challenging than imag…