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Driver Drowsiness Estimation Based on Factorized Bilinear Feature Fusion and a Long-Short-Term Recurrent Convolutional Network

Shuang Chen, Zengcai Wang, Wenxin Chen
2020 Information  
To solve these problems, we propose a driver sleepiness estimation model based on factorized bilinear feature fusion and a long- short-term recurrent convolutional network to detect driver drowsiness efficiently  ...  Then, based on the factorized bilinear feature fusion model, we performed a nonlinear fusion of the deep feature representations of the eyes and mouth.  ...  To solve these problems, we propose a driver drowsiness estimation model based on factorized bilinear feature fusion and a long-short-term recurrent convolutional network to detect driver sleepiness effectively  ... 
doi:10.3390/info12010003 fatcat:czit33rpd5awbfsn7fw5gcdckq

Front Matter: Volume 10615

Hui Yu, Junyu Dong
2018 Ninth International Conference on Graphic and Image Processing (ICGIP 2017)  
using a Base 36 numbering system employing both numerals and letters.  ...  The papers in this volume were part of the technical conference cited on the cover and title page. Papers were selected and subject to review by the editors and conference program committee.  ...  card using recurrent neural network [10615-133] 10615 17 Object recognition in images via a factor graph model [10615-146] 10615 18 An effective method for cirrhosis recognition based on multi-feature  ... 
doi:10.1117/12.2316542 fatcat:tdaw76jq6nehpnttiga2lcuhna

2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30

2020 IEEE transactions on circuits and systems for video technology (Print)  
Zhang, X., TCSVT Jan. 2020 217-231 Hu, X., see Zhu, L., TCSVT Oct. 2020 3358-3371 Hu, Y., Lu, M., Xie, C., and Lu, X  ...  ., see Sepas-Moghaddam, A., TCSVT Dec. 2020 4496-4512 Hassanpour, H., see Khosravi, M.H., TCSVT Jan. 2020 48-58 Hatzinakos, D., see 2900-2916 Hayat, M., see 2900-2916 He, C., Hu, Y., Chen, Y., Fan  ...  Guo, J., +, TCSVT Nov. 2020 4355-4367 Streaming Video QoE Modeling and Prediction: A Long Short-Term Memory Approach.  ... 
doi:10.1109/tcsvt.2020.3043861 fatcat:s6z4wzp45vfflphgfcxh6x7npu

Object Detection, Distributed Cloud Computing and Parallelization Techniques for Autonomous Driving Systems

Edgar Cortés Gallardo Medina, Victor Miguel Velazquez Espitia, Daniela Chípuli Silva, Sebastián Fernández Ruiz de las Cuevas, Marco Palacios Hirata, Alfredo Zhu Chen, José Ángel González González, Rogelio Bustamante-Bello, Carlos Francisco Moreno-García
2021 Applied Sciences  
Our findings show that while techniques such as convolutional neural networks, recurrent neural networks, and long short-term memory can effectively handle the initial detection and path planning tasks  ...  Additionally, we have mapped different strategies to handle the parallelization task, both within and between the networks.  ...  LSTM Long Short-Term Memory (LSTM) is a recurrent-type cell for regressive NN. LSTMs are explicitly designed to avoid long-term dependency.  ... 
doi:10.3390/app11072925 fatcat:dssfxpdh6zd6bplnrctmob2mre

Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021 [article]

Karl-Herbert Schäfer
2021 arXiv   pre-print
The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe  ...  , Offenburg and Trier, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes \'ecoles' in the fields of engineering, architecture  ...  Wetzel and T. Iraki for helpful comments and discussion.  ... 
arXiv:2112.05657v1 fatcat:wdjgymicyrfybg5zth2dc2i3ni

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
......... 882 FASLIP1: Feature Selection/Image Analysis, Chair: Qi Chen Bing Xue Driver Drowsiness Classification Based on Eye Blink and Head Movement Features Using the k-NN Algorithm Mariella Dreissig  ...  Programming Abigail McGhie, Bing Xue and Mengjie Zhang .......... 2684 Evolutionary Design of Long Short Term Memory (LSTM) Ensemble Ramya Anasseriyil Viswambaran, Gang Chen, Bing Xue and Mohammad Nekooei  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

Discrimination of short speech‐like formant transitions

Astrid van Wieringen, Louis C. W. Pols
1992 Journal of the Acoustical Society of America  
In all cases, the waveforms are reasonably well predicted by a simple and efficient convolution technique.  ...  Speech perception in newborns thus requires two processes: the multidimensional space of the utterances is defined in terms of distinctive features, requiring a large number of presentations.  ...  Such an array could be suitable for a long-term vent field monitor.  ... 
doi:10.1121/1.405128 fatcat:dbtewzqvijhkta6op7ul3ribti

Danish activities concerning noise in the environment

Fritz Ingerslev
1982 Journal of the Acoustical Society of America  
Long experience with estimating human responses to noise from sound level meter readings has led to the general' use of the A-weighting network alone for many purposes.  ...  One can do a Fourier transformation of the result and then express the convolution as the product of z--transforms.  ...  [ Chimpanzees observed in Tanzania produced a graded, dynamic sound system ranging from short distance, softer, lower F 0 sounds to long distance, louder, higher F0 sounds.  ... 
doi:10.1121/1.2019901 fatcat:kk6boa5no5aitorvgbktvdlxou

Machine Learning and Image Processing for Clinical Outcome Prediction: Applications in Medical Data from Patients with Traumatic Brain Injury, Ulcerative Colitis, and Heart Failure [article]

Heming Yao, University, My
While the human's interpretation of medical images is subjective and qualitative, AI-based models can analyze those data in a more reproducible, quantitative, and less expensive way.  ...  Features with clinical meaning and models that can be well explained can gain more trust and are more favorable to end-users.  ...  In [103] , temporal information among consecutive frames was explored by a long-short-term-memory layer to improve the accuracy of pose estimation.  ... 
doi:10.7302/3828 fatcat:xgtrlqpebnf7lmxv5sbguf3jpq

Proceedings of the 13th Russian German Conference on Biomedical Engineering

Steffen Leonhardt, Steffen Leonhardt
Acknowledgements J.Ch.S. is grateful for a stipend and financial support for this project from Prince of Songkla University, Thailand.  ...  Acknowledgment This work was provided by the Ministry of Education and Science of the Russian Federation (Agreement 14.575. 21 Proceedings of the Russian German Conference on Biomedical Engineering  ...  While long short-term memory (LSTM) network is a special kind of recurrent neural network (RNN) with a smart dynamical feedback structure to form short memory in the networks.  ... 
doi:10.18154/rwth-2018-224393 fatcat:vu735cealrczzc7aiwmzojoczm