Search Results for author: Naifan Zhuang

Found 4 papers, 0 papers with code

Differential Recurrent Neural Network and its Application for Human Activity Recognition

no code implementations9 May 2019 Naifan Zhuang, Guo-Jun Qi, The Duc Kieu, Kien A. Hua

The Long Short-Term Memory (LSTM) recurrent neural network is capable of processing complex sequential information since it utilizes special gating schemes for learning representations from long input sequences.

Human Activity Recognition Time Series +1

Deep Segment Hash Learning for Music Generation

no code implementations30 May 2018 Kevin Joslyn, Naifan Zhuang, Kien A. Hua

Music generation research has grown in popularity over the past decade, thanks to the deep learning revolution that has redefined the landscape of artificial intelligence.

Music Generation

Deep Differential Recurrent Neural Networks

no code implementations11 Apr 2018 Naifan Zhuang, The Duc Kieu, Guo-Jun Qi, Kien A. Hua

The proposed model progressively builds up the ability of the LSTM gates to detect salient dynamical patterns in deeper stacked layers modeling higher orders of DoS, and thus the proposed LSTM model is termed deep differential Recurrent Neural Network (d2RNN).

Temporal Sequences

Differential Recurrent Neural Networks for Action Recognition

no code implementations ICCV 2015 Vivek Veeriah, Naifan Zhuang, Guo-Jun Qi

This change in information gain is quantified by Derivative of States (DoS), and thus the proposed LSTM model is termed as differential Recurrent Neural Network (dRNN).

Action Recognition Temporal Action Localization +2

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