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Concept

Highway network

Related publications (27)

Feed-forwards meet recurrent networks in vehicle trajectory prediction

Alexandre Massoud Alahi, Mohammadhossein Bahari

For an autonomous car, getting surprised is the worst thing that can happen. To prevent that, plenty of studies are trying to forecast traffic participants’ actions especially in an urban scene using recurrent networks. Recurrent networks are used for temp ...

2019

A comparative study on wavelets and residuals in deep super resolution

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou, Fayez Lahoud

Despite the advances in single-image super resolution using deep convolutional networks, the main problem remains unsolved: recovering fine texture details. Recent works in super resolution aim at modifying the training of neural networks to enable the rec ...

2019

The Unfolding Argument: Why Recurrent Processing Cannot Explain Consciousness

Michael Herzog, Adrien Christophe Doerig, Aaron Schurger

Neuroscientific theories aim to explain paradigm cases of consciousness such as masking, binocular rivalry or the transition from dreamless sleep to wakefulness. The most popular theories are based on computational principles. Recurrent processing is a key ...

2018

Deep Residual Network for Joint Demosaicing and Super- Resolution

Sabine Süsstrunk, Radhakrishna Achanta, Ruofan Zhou

The two classic image restoration tasks, demosaicing and super-resolution, have traditionally always been studied indepen- dently. That is sub-optimal as sequential processing, demosaic- ing and then super-resolution, may lead to amplification of ar- tifac ...

Society for Imaging Science and Technology ( IS&T )2018

Combining Multiple Views for Visual Speech Recognition

Jean-Philippe Thiran, Hazim Kemal Ekenel, Marina Zimmermann

Visual speech recognition is a challenging research problem with a particular practical application of aiding audio speech recognition in noisy scenarios. Multiple camera setups can be beneficial for the visual speech recognition systems in terms of improv ...

KTH2017

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

Wulfram Gerstner, Aditya Gilra

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedfo ...

Elife Sciences Publications Ltd2017

Deep Convolutional Neural Network for Inverse Problems in Imaging

Michaël Unser, Michael Thompson McCann, Kyong Hwan Jin, Emmanuel Augustin Julien Froustey

In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades. ...

2017