Prediction of Real-World Slope Movements via Recurrent and Non-recurrent Neural Network Algorithms: A Case Study of the Tangni Landslide

2021 ◽  
Author(s):  
Praveen Kumar ◽  
Priyanka Sihag ◽  
Abhijeet Sharma ◽  
Ankush Pathania ◽  
Ravinder Singh ◽  
...  
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Real World ◽  
Network Algorithms ◽  
Slope Movements

Recurrent Neural Network and random forest for analysis and accurate forecast of atmospheric pollutants: A case study in Hangzhou, China

2019 ◽  
Vol 231 ◽  
pp. 1005-1015 ◽  
Author(s):  
Rui Feng ◽  
Hui-jun Zheng ◽  
Han Gao ◽  
An-ran Zhang ◽  
Chong Huang ◽  
...  
Keyword(s):  
Neural Network ◽  
Random Forest ◽  
Recurrent Neural Network ◽  
Atmospheric Pollutants ◽  
Accurate Forecast

SpeeChin

2021 ◽  
Vol 5 (4) ◽  
pp. 1-23
Author(s):  
Ruidong Zhang ◽  
Mingyang Chen ◽  
Benjamin Steeper ◽  
Yaxuan Li ◽  
Zihan Yan ◽  
...  
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Real World ◽  
User Study ◽  
Imaging System ◽  
User Studies ◽  
Ir Imaging ◽  
Real World Applications ◽  
Challenges And Opportunities ◽  
Silent Speech

This paper presents SpeeChin, a smart necklace that can recognize 54 English and 44 Chinese silent speech commands. A customized infrared (IR) imaging system is mounted on a necklace to capture images of the neck and face from under the chin. These images are first pre-processed and then deep learned by an end-to-end deep convolutional-recurrent-neural-network (CRNN) model to infer different silent speech commands. A user study with 20 participants (10 participants for each language) showed that SpeeChin could recognize 54 English and 44 Chinese silent speech commands with average cross-session accuracies of 90.5% and 91.6%, respectively. To further investigate the potential of SpeeChin in recognizing other silent speech commands, we conducted another study with 10 participants distinguishing between 72 one-syllable nonwords. Based on the results from the user studies, we further discuss the challenges and opportunities of deploying SpeeChin in real-world applications.

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