Journal articles on the topic 'Convolutional recurrent neural networks'
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Hindarto, Djarot. "Comparison of RNN Architectures and Non-RNN Architectures in Sentiment Analysis." sinkron 8, no. 4 (October 1, 2023): 2537–46. http://dx.doi.org/10.33395/sinkron.v8i4.13048.
Kassylkassova, Kamila, Zhanna Yessengaliyeva, Gayrat Urazboev, and Ayman Kassylkassova. "OPTIMIZATION METHOD FOR INTEGRATION OF CONVOLUTIONAL AND RECURRENT NEURAL NETWORK." Eurasian Journal of Mathematical and Computer Applications 11, no. 2 (2023): 40–56. http://dx.doi.org/10.32523/2306-6172-2023-11-2-40-56.
Lyu, Shengfei, and Jiaqi Liu. "Convolutional Recurrent Neural Networks for Text Classification." Journal of Database Management 32, no. 4 (October 2021): 65–82. http://dx.doi.org/10.4018/jdm.2021100105.
P., Vijay Babu, and Senthil Kumar R. "Performance Evaluation of Brain Tumor Identification and Examination Using MRI Images with Innovative Convolution Neural Networks and Comparing the Accuracy with RNN Algorithm." ECS Transactions 107, no. 1 (April 24, 2022): 12405–14. http://dx.doi.org/10.1149/10701.12405ecst.
Peng, Wenli, Shenglai Zhen, Xin Chen, Qianjing Xiong, and Benli Yu. "Study on convolutional recurrent neural networks for speech enhancement in fiber-optic microphones." Journal of Physics: Conference Series 2246, no. 1 (April 1, 2022): 012084. http://dx.doi.org/10.1088/1742-6596/2246/1/012084.
P, Suma, and Senthil Kumar R. "Automatic Classification of Normal and Infected Blood Cells for Leukemia Through Color Based Segmentation Technique Over Innovative CNN Algorithm and Comparing the Error Rate with RNN." ECS Transactions 107, no. 1 (April 24, 2022): 14123–34. http://dx.doi.org/10.1149/10701.14123ecst.
Wang, Lin, and Zuqiang Meng. "Multichannel Two-Dimensional Convolutional Neural Network Based on Interactive Features and Group Strategy for Chinese Sentiment Analysis." Sensors 22, no. 3 (January 18, 2022): 714. http://dx.doi.org/10.3390/s22030714.
Poudel, Sushan, and Dr R. Anuradha. "Speech Command Recognition using Artificial Neural Networks." JOIV : International Journal on Informatics Visualization 4, no. 2 (May 26, 2020): 73. http://dx.doi.org/10.30630/joiv.4.2.358.
Wu, Hao, and Saurabh Prasad. "Convolutional Recurrent Neural Networks forHyperspectral Data Classification." Remote Sensing 9, no. 3 (March 21, 2017): 298. http://dx.doi.org/10.3390/rs9030298.
Li, Kezhi, John Daniels, Chengyuan Liu, Pau Herrero, and Pantelis Georgiou. "Convolutional Recurrent Neural Networks for Glucose Prediction." IEEE Journal of Biomedical and Health Informatics 24, no. 2 (February 2020): 603–13. http://dx.doi.org/10.1109/jbhi.2019.2908488.
Zhang, Zao, and Yuan Dong. "Temperature Forecasting via Convolutional Recurrent Neural Networks Based on Time-Series Data." Complexity 2020 (March 20, 2020): 1–8. http://dx.doi.org/10.1155/2020/3536572.
Nguyen, Viet-Hung, Minh-Tuan Nguyen, Jeongsik Choi, and Yong-Hwa Kim. "NLOS Identification in WLANs Using Deep LSTM with CNN Features." Sensors 18, no. 11 (November 20, 2018): 4057. http://dx.doi.org/10.3390/s18114057.
Shchetinin, E. Yu. "EMOTIONS RECOGNITION IN HUMAN SPEECH USING DEEP NEURAL NETWORKS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 199 (January 2021): 44–51. http://dx.doi.org/10.14489/vkit.2021.01.pp.044-051.
Hou, Kai. "Principal Component Analysis and Prediction of Students’ Physical Health Standard Test Results Based on Recurrent Convolution Neural Network." Wireless Communications and Mobile Computing 2021 (September 4, 2021): 1–11. http://dx.doi.org/10.1155/2021/2438656.
D, Sreekanth. "Metro Water Fraudulent Prediction in Houses Using Convolutional Neural Network and Recurrent Neural Network." Revista Gestão Inovação e Tecnologias 11, no. 4 (July 10, 2021): 1177–87. http://dx.doi.org/10.47059/revistageintec.v11i4.2177.
Ma, Hao, Chao Chen, Qing Zhu, Haitao Yuan, Liming Chen, and Minglei Shu. "An ECG Signal Classification Method Based on Dilated Causal Convolution." Computational and Mathematical Methods in Medicine 2021 (February 2, 2021): 1–10. http://dx.doi.org/10.1155/2021/6627939.
R, Gayathri, Lydia Beryl D, Gowtham M, Naveen Kumar N, and Dr M. S. Anbarasi. "Detection and Classification of Cyberbullying Using CR*." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 24–29. http://dx.doi.org/10.22214/ijraset.2023.49984.
Guo, Yanbu, Bingyi Wang, Weihua Li, and Bei Yang. "Protein secondary structure prediction improved by recurrent neural networks integrated with two-dimensional convolutional neural networks." Journal of Bioinformatics and Computational Biology 16, no. 05 (October 2018): 1850021. http://dx.doi.org/10.1142/s021972001850021x.
Pan, Yumin. "Different Types of Neural Networks and Applications: Evidence from Feedforward, Convolutional and Recurrent Neural Networks." Highlights in Science, Engineering and Technology 85 (March 13, 2024): 247–55. http://dx.doi.org/10.54097/6rn1wd81.
Z, Farhan, Kavipriya A, Abinaya C, and Ezhilarasan M. "Enhanced Image Segmentation Using Convolutional Recurrent Neural Networks." International Innovative Research Journal of Engineering and Technology 5, no. 3 (March 30, 2020): 78–83. http://dx.doi.org/10.32595/iirjet.org/v5i3.2020.118.
Albaqshi, Hussain, and Alaa Sagheer. "Dysarthric Speech Recognition using Convolutional Recurrent Neural Networks." International Journal of Intelligent Engineering and Systems 13, no. 6 (December 31, 2020): 384–92. http://dx.doi.org/10.22266/ijies2020.1231.34.
Santacroce, Michael, Daniel Koranek, and Rashmi Jha. "Detecting Malicious Assembly using Convolutional, Recurrent Neural Networks." Advances in Science, Technology and Engineering Systems Journal 4, no. 5 (2019): 46–52. http://dx.doi.org/10.25046/aj040506.
Gayathri, P., P. Gowri Priya, L. Sravani, Sandra Johnson, and Visanth Sampath. "Convolutional Recurrent Neural Networks Based Speech Emotion Recognition." Journal of Computational and Theoretical Nanoscience 17, no. 8 (August 1, 2020): 3786–89. http://dx.doi.org/10.1166/jctn.2020.9321.
Hu, Wenjin, Jiawei Xiong, Ning Wang, Feng Liu, Yao Kong, and Chaozhong Yang. "Integrated Model Text Classification Based on Multineural Networks." Electronics 13, no. 2 (January 22, 2024): 453. http://dx.doi.org/10.3390/electronics13020453.
Huang, Feizhen, Jinfang Zeng, Yu Zhang, and Wentao Xu. "Convolutional recurrent neural networks with multi-sized convolution filters for sound-event recognition." Modern Physics Letters B 34, no. 23 (April 25, 2020): 2050235. http://dx.doi.org/10.1142/s0217984920502358.
Kim, Deageon. "Research On Text Classification Based On Deep Neural Network." International Journal of Communication Networks and Information Security (IJCNIS) 14, no. 1s (December 31, 2022): 100–113. http://dx.doi.org/10.17762/ijcnis.v14i1s.5618.
Khan, Muhammad Ashfaq. "HCRNNIDS: Hybrid Convolutional Recurrent Neural Network-Based Network Intrusion Detection System." Processes 9, no. 5 (May 10, 2021): 834. http://dx.doi.org/10.3390/pr9050834.
Solovyeva, Elena, and Ali Abdullah. "Binary and Multiclass Text Classification by Means of Separable Convolutional Neural Network." Inventions 6, no. 4 (October 19, 2021): 70. http://dx.doi.org/10.3390/inventions6040070.
Rymarczyk, T., D. Wójcik, Ł. Maciura, W. Rosa, and M. Bartosik. "Body surface potential mapping time series recognition using convolutional and recurrent neural networks." Journal of Physics: Conference Series 2408, no. 1 (December 1, 2022): 012001. http://dx.doi.org/10.1088/1742-6596/2408/1/012001.
Wan, Renzhuo, Shuping Mei, Jun Wang, Min Liu, and Fan Yang. "Multivariate Temporal Convolutional Network: A Deep Neural Networks Approach for Multivariate Time Series Forecasting." Electronics 8, no. 8 (August 7, 2019): 876. http://dx.doi.org/10.3390/electronics8080876.
Casabianca, Pietro, and Yu Zhang. "Acoustic-Based UAV Detection Using Late Fusion of Deep Neural Networks." Drones 5, no. 3 (June 26, 2021): 54. http://dx.doi.org/10.3390/drones5030054.
Xu, Zhijing, Yuhao Huo, Kun Liu, and Sidong Liu. "Detection of ship targets in photoelectric images based on an improved recurrent attention convolutional neural network." International Journal of Distributed Sensor Networks 16, no. 3 (March 2020): 155014772091295. http://dx.doi.org/10.1177/1550147720912959.
Liu, Xuanxin, Fu Xu, Yu Sun, Haiyan Zhang, and Zhibo Chen. "Convolutional Recurrent Neural Networks for Observation-Centered Plant Identification." Journal of Electrical and Computer Engineering 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/9373210.
Kwak, Jin-Yeol, and Yong-Joo Chung. "Sound Event Detection Using Derivative Features in Deep Neural Networks." Applied Sciences 10, no. 14 (July 17, 2020): 4911. http://dx.doi.org/10.3390/app10144911.
Wang, Weiping, Feng Zhang, Xi Luo, and Shigeng Zhang. "PDRCNN: Precise Phishing Detection with Recurrent Convolutional Neural Networks." Security and Communication Networks 2019 (October 29, 2019): 1–15. http://dx.doi.org/10.1155/2019/2595794.
Chen, Jingwen, Yingwei Pan, Yehao Li, Ting Yao, Hongyang Chao, and Tao Mei. "Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8167–74. http://dx.doi.org/10.1609/aaai.v33i01.33018167.
Liang, Kaiwei, Na Qin, Deqing Huang, and Yuanzhe Fu. "Convolutional Recurrent Neural Network for Fault Diagnosis of High-Speed Train Bogie." Complexity 2018 (October 23, 2018): 1–13. http://dx.doi.org/10.1155/2018/4501952.
Wang, Guanchao. "Analysis of sentiment analysis model based on deep learning." Applied and Computational Engineering 5, no. 1 (June 14, 2023): 750–56. http://dx.doi.org/10.54254/2755-2721/5/20230694.
Yüksel, Kıvanç, and Władysław Skarbek. "Convolutional and Recurrent Neural Networks for Face Image Analysis." Foundations of Computing and Decision Sciences 44, no. 3 (September 1, 2019): 331–47. http://dx.doi.org/10.2478/fcds-2019-0017.
Liu, Nan. "Study on the Application of Improved Audio Recognition Technology Based on Deep Learning in Vocal Music Teaching." Mathematical Problems in Engineering 2022 (August 18, 2022): 1–12. http://dx.doi.org/10.1155/2022/1002105.
Le, Viet-Tuan, Kiet Tran-Trung, and Vinh Truong Hoang. "A Comprehensive Review of Recent Deep Learning Techniques for Human Activity Recognition." Computational Intelligence and Neuroscience 2022 (April 20, 2022): 1–17. http://dx.doi.org/10.1155/2022/8323962.
Cheng, Yepeng, Zuren Liu, and Yasuhiko Morimoto. "Attention-Based SeriesNet: An Attention-Based Hybrid Neural Network Model for Conditional Time Series Forecasting." Information 11, no. 6 (June 5, 2020): 305. http://dx.doi.org/10.3390/info11060305.
Fantaye, Tessfu Geteye, Junqing Yu, and Tulu Tilahun Hailu. "Advanced Convolutional Neural Network-Based Hybrid Acoustic Models for Low-Resource Speech Recognition." Computers 9, no. 2 (May 2, 2020): 36. http://dx.doi.org/10.3390/computers9020036.
Zhao, Ping, Zhijie Fan*, Zhiwei Cao, and Xin Li. "Intrusion Detection Model Using Temporal Convolutional Network Blend Into Attention Mechanism." International Journal of Information Security and Privacy 16, no. 1 (January 2022): 1–20. http://dx.doi.org/10.4018/ijisp.290832.
Fabien-Ouellet, Gabriel, and Rahul Sarkar. "Seismic velocity estimation: A deep recurrent neural-network approach." GEOPHYSICS 85, no. 1 (December 19, 2019): U21—U29. http://dx.doi.org/10.1190/geo2018-0786.1.
Li, Haoliang, Shiqi Wang, and AlexC Kot. "Image Recapture Detection with Convolutional and Recurrent Neural Networks." Electronic Imaging 2017, no. 7 (January 29, 2017): 87–91. http://dx.doi.org/10.2352/issn.2470-1173.2017.7.mwsf-329.
Shang, Jin, and Mingxuan Sun. "Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 4878–85. http://dx.doi.org/10.1609/aaai.v33i01.33014878.
Qin, Chen, Jo Schlemper, Jose Caballero, Anthony N. Price, Joseph V. Hajnal, and Daniel Rueckert. "Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction." IEEE Transactions on Medical Imaging 38, no. 1 (January 2019): 280–90. http://dx.doi.org/10.1109/tmi.2018.2863670.
Zuo, Zhen, Bing Shuai, Gang Wang, Xiao Liu, Xingxing Wang, Bing Wang, and Yushi Chen. "Learning Contextual Dependence With Convolutional Hierarchical Recurrent Neural Networks." IEEE Transactions on Image Processing 25, no. 7 (July 2016): 2983–96. http://dx.doi.org/10.1109/tip.2016.2548241.
Cakir, Emre, Giambattista Parascandolo, Toni Heittola, Heikki Huttunen, and Tuomas Virtanen. "Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection." IEEE/ACM Transactions on Audio, Speech, and Language Processing 25, no. 6 (June 2017): 1291–303. http://dx.doi.org/10.1109/taslp.2017.2690575.