# [PDF] Top 20 Emotion Recognition with Deep Neural Networks

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### Emotion Recognition with Deep Neural Networks

... modalities **with** recurrent **networks** (Chen and Jin, 2015; He et ...deal **with** challenges arising from different temporal resolutions of ...applying **deep** learning methods to **emotion** ... Voir le document complet

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### Leveraging deep neural networks with nonnegative representations for improved environmental sound classification

... 25], **with** the goal of augmenting the general- ization power of the network by training its weights according to a data reconstruction loss (mean squared ...of **neural** **networks**, the weights here are ... Voir le document complet

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### Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

... ‘‘**deep** **neural** **networks**’’ share many properties **with** these bio-inspired ...object **recognition** systems have been produced that utilize **deep** **neural** **networks** and have ... Voir le document complet

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### Contributions to handwriting recognition using deep neural networks and quantum computation

... classical **neural** **networks** obtain state of the art performance for many tasks, while work on quantum **neural** **networks** is only in its ...classical-quantum **neural** **networks**, including ... Voir le document complet

196

### Multichannel audio source separation with deep neural networks

... where **deep** **neural** **networks** (DNNs) are used to model the source spectra and combined **with** the classical multichannel Gaussian model to exploit the spatial ... Voir le document complet

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### A brief introduction to multichannel noise reduction with deep neural networks

... A brief introduction to multichannel noise reduction with deep neural networks.. Romain Serizel.[r] ... Voir le document complet

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### Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks

... years, **deep** learning based approaches achieved outstanding results in image **recognition** and ...Among **deep** learning-based models for action **recognition**, Convolutional **Neural** ... Voir le document complet

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### Multichannel Music Separation with Deep Neural Networks

... Recent studies have shown that **deep** **neural** **networks** (DNNs) are able to model complex functions and perform well on various tasks [4]. Many studies have addressed the problem of single-channel source ... Voir le document complet

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### Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

... ORK **Deep** model for computer vision and natural ...the **deep** **neural** network developed rapidly in recent years in both the field of computer vision and natural lan- ...a **deep** Convolutional ... Voir le document complet

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### On The Fly Generated Data for Industrial Part Orientation Estimation with Deep Neural Networks

... estimation, **deep** **neural** **networks**, convolutional **neural** **networks**, depth estimation, industrial parts, rendered data ...picking **with** robotic ...convolutional **neural** ... Voir le document complet

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### New Paradigm in Speech Recognition: Deep Neural Networks

... 2012, **deep** learning has shown excellent results in many domains: image **recognition**, speech **recognition**, language modelling, parsing, information retrieval, speech synthesis, translation, autonomous ... Voir le document complet

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### Contributions to handwriting recognition using deep neural networks and quantum computing

... classical **neural** **networks** obtain state of the art performance for many tasks, while work on quantum **neural** **networks** is only in its ...classical-quantum **neural** **networks**, including ... Voir le document complet

196

### Acoustic models for speech recognition using Deep Neural Networks based on approximate math

... been **Deep** **Neural** **Networks** ...speech **recognition** community. For Automatic Speech **Recognition** (ASR), DNN-based models result in 10-30% relative improvement in word error rates over ... Voir le document complet

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### On the CVP for the root lattices via folding with deep ReLU neural networks

... of **deep** **neural** **networks** focuses mostly on (i) [7][11], by studying some specific functions contained in the function class of a ...a **deep** network **with** a polynomial number of parameters ... Voir le document complet

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### Deep neural networks for audio scene recognition

... artificial **neural** **networks** (ANN) have known a renewed interest since efficient training procedures have emerged to learn the so called **deep** **neural** **networks** (DNN), ...ANN **with** at ... Voir le document complet

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### Sous-continents Estimation of Emotion in Music with Recurrent Neural Networks

... real-valued **emotion** dimensions, namely valence and arousal, in a time-continuous ...recurrent **neural** **networks** (RNN) for their sequence mod- eling ...subset. **With** the baseline set of 260 acous- ... Voir le document complet

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### Time-continuous Estimation of Emotion in Music with Recurrent Neural Networks

... real-valued **emotion** dimensions, namely valence and arousal, in a time-continuous ...recurrent **neural** **networks** (RNN) for their sequence mod- eling ...subset. **With** the baseline set of 260 acous- ... Voir le document complet

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### Deep Background Subtraction with Scene-Specific Convolutional Neural Networks

... performed **with** max- pooling instead of averaging and hidden sigmoid units are replaced **with** rectified linear units for faster ...fields **with** a 1x1 stride for all convolutional layers (see red patches ... Voir le document complet

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### Clinical event prediction and understanding with deep neural networks

... In addition, we compare these representations along with both long short-term memory networks (LSTM) and convolutional neural networks (CNN) for prediction of five i[r] ... Voir le document complet

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### Deep neural networks with transfer learning in millet crop images

... 1. Introduction Pearl millet is one the most important food crop in Mali and tropical. Millet diseases are important items in the reduction of quality and quantity in crop millet. Therefore, the detection and diagnosis ... Voir le document complet

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