G2P conversion based on (a) convolutional neural network with residual connections (CNN+RES) and (b) encoder convolutional neural network with residual connections and decoder

Multi-font Printed Chinese Character Recognition using Multi-pooling Convolutional

5 Results obtained with 14 MFCC features on the single channel model with two different offset values.. TL =

Motivated by the recent successes in natural image colorization based on deep learning techniques, we investigate the colorization problem at the cartoon domain using

Under the sustainability today, almost everyone understands the environmentally friendly use of energy-efficient solutions, which are alternatives to private transport

Thesis point IV: Classification based on Dynamic Time Warping distance and path length combined with a convolutional neural network specifically designed for

[23] trained a Convolutional Neural Network to map from a grayscale input to a distribution of quantized color values.. This algorithm was evaluated with the help of human

Continuous vocoder parameters (ContF0, Maximum Voiced Frequency and Mel-Generalized Cepstrum) are predicted using a convolutional neural network, with UTI as input.. The

Continuous vocoder parameters (ContF0, Maximum Voiced Frequency and Mel-Generalized Cepstrum) are predicted using a convolutional neural network, with UTI as input.. The

CONCLUSION AND OUTLOOK The presented convolutional neural network was successful in learning abstractions from velocity fields by being able to predict the stagnating flow in a

In [13], the authors proposed a joint deep learning framework and a new deep network architecture that jointly learns feature extraction, deformation handling, occlusion handling,

In [13], the authors proposed a joint deep learning framework and a new deep network architecture that jointly learns feature extraction, deformation handling, occlusion handling,

An ef- ficient end-to-end supervised learning framework is presented for fast image retrieval that learns probability-based semantic- level similarity and feature-level

I have developed a method based on backtracking search that provides all of the suitable convolutional neural network architectures at a given input, layer number, and memory

Keywords: Spoken Language Understanding (SLU), intent detection, Convolutional Neural Networks, residual connections, deep learning, neural networks.. 1

In the proposed approach for semantic labeling of dense point clouds, we have considered the characteristic of the data and we have proposed a two-channel 3D convolutional

The predictive initializer is based on a convolutional deep neural network, wherewith the velocity fields in the fluid domain can be predicted for a specific geometry as depicted

The training process for the interconnected model operated the same as the separate training process. The only difference was the interconnected model trains three