The effectiveness of using a pretrained deep learning neural networks for object classification in underwater video
Video image processing and object classification using a Deep Learning Neural Network
(DLNN) can significantly increase the autonomy of underwater vehicles. This paper …
(DLNN) can significantly increase the autonomy of underwater vehicles. This paper …
Voiceprint identification for limited dataset using the deep migration hybrid model based on transfer learning
C Sun, Y Yang, C Wen, K **e, F Wen - Sensors, 2018 - mdpi.com
The convolutional neural network (CNN) has made great strides in the area of voiceprint
recognition; but it needs a huge number of data samples to train a deep neural network. In …
recognition; but it needs a huge number of data samples to train a deep neural network. In …
[PDF][PDF] Assessing the degree of nativeness and Parkinson's condition using Gaussian processes and deep rectifier neural networks
Abstract The Interspeech 2015 Computational Paralinguistics Challenge includes two
regression learning tasks, namely the Parkinson's Condition Sub-Challenge and the Degree …
regression learning tasks, namely the Parkinson's Condition Sub-Challenge and the Degree …
Laughter classification using Deep Rectifier Neural Networks with a minimal feature subset
Laughter is one of the most important paralinguistic events, and it has specific roles in
human conversation. The automatic detection of laughter occurrences in human speech can …
human conversation. The automatic detection of laughter occurrences in human speech can …
[PDF][PDF] Detecting the intensity of cognitive and physical load using AdaBoost and Deep Rectifier Neural Networks
Abstract The Interspeech ComParE 2014 Challenge consists of two machine learning tasks,
which have quite a small number of examples. Due to our good results in ComParE 2013 …
which have quite a small number of examples. Due to our good results in ComParE 2013 …
Automatic close captioning for live hungarian television broadcast speech: A fast and resource-efficient approach
In this paper, the application of LVCSR (Large Vocabulary Continuous Speech Recognition)
technology is investigated for real-time, resource-limited broadcast close captioning. The …
technology is investigated for real-time, resource-limited broadcast close captioning. The …
QR code localization using deep neural networks
Usage of computer-readable visual codes became common in our everyday life at industrial
environments and private use. The reading process of visual codes consists of two steps …
environments and private use. The reading process of visual codes consists of two steps …
[PDF][PDF] Enhancing constructive neural network performance using functionally expanded input data
Constructive learning algorithms are an efficient way to train feedforward neural networks.
Some of their features, such as the automatic definition of the neural network (NN) …
Some of their features, such as the automatic definition of the neural network (NN) …
Efficient visual code localization with neural networks
The use of computer-readable visual codes became common in our everyday life both in
industrial environments and for private use. The reading process of visual codes consists of …
industrial environments and for private use. The reading process of visual codes consists of …
[PDF][PDF] Domain adaptation of deep neural networks for automatic speech recognition via wireless sensors
Wireless sensors are recent, portable, low-powered devices, designed to record and
transmit observations of their environment such as speech. To allow portability they are …
transmit observations of their environment such as speech. To allow portability they are …