Статті в журналах з теми "CNN AND LSTM NETWORKS"
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Garcia, Carlos Iturrino, Francesco Grasso, Antonio Luchetta, Maria Cristina Piccirilli, Libero Paolucci, and Giacomo Talluri. "A Comparison of Power Quality Disturbance Detection and Classification Methods Using CNN, LSTM and CNN-LSTM." Applied Sciences 10, no. 19 (September 27, 2020): 6755. http://dx.doi.org/10.3390/app10196755.
Повний текст джерелаXu-Nan Tan, Xu-Nan Tan. "Human Activity Recognition Based on CNN and LSTM." 電腦學刊 34, no. 3 (June 2023): 221–35. http://dx.doi.org/10.53106/199115992023063403016.
Повний текст джерелаLiu, Tianyuan, Jinsong Bao, Junliang Wang, and Yiming Zhang. "A Hybrid CNN–LSTM Algorithm for Online Defect Recognition of CO2 Welding." Sensors 18, no. 12 (December 10, 2018): 4369. http://dx.doi.org/10.3390/s18124369.
Повний текст джерелаGeng, Yue, Lingling Su, Yunhong Jia, and Ce Han. "Seismic Events Prediction Using Deep Temporal Convolution Networks." Journal of Electrical and Computer Engineering 2019 (April 2, 2019): 1–14. http://dx.doi.org/10.1155/2019/7343784.
Повний текст джерелаBanda, Anish. "Image Captioning using CNN and LSTM." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (August 31, 2021): 2666–69. http://dx.doi.org/10.22214/ijraset.2021.37846.
Повний текст джерелаReddy, V. Varshith, Y. Shiva Krishna, U. Varun Kumar Reddy, and Shubhangi Mahule. "Gray Scale Image Captioning Using CNN and LSTM." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 1566–71. http://dx.doi.org/10.22214/ijraset.2022.41589.
Повний текст джерелаZhang, Jilin, Lishi Ye, and Yongzeng Lai. "Stock Price Prediction Using CNN-BiLSTM-Attention Model." Mathematics 11, no. 9 (April 23, 2023): 1985. http://dx.doi.org/10.3390/math11091985.
Повний текст джерелаYang, Xingyu, and Zhongrong Zhang. "A CNN-LSTM Model Based on a Meta-Learning Algorithm to Predict Groundwater Level in the Middle and Lower Reaches of the Heihe River, China." Water 14, no. 15 (July 31, 2022): 2377. http://dx.doi.org/10.3390/w14152377.
Повний текст джерелаSridhar, C., and Aniruddha Kanhe. "Performance Comparison of Various Neural Networks for Speech Recognition." Journal of Physics: Conference Series 2466, no. 1 (March 1, 2023): 012008. http://dx.doi.org/10.1088/1742-6596/2466/1/012008.
Повний текст джерелаXu, Lingfeng, Xiang Chen, Shuai Cao, Xu Zhang, and Xun Chen. "Feasibility Study of Advanced Neural Networks Applied to sEMG-Based Force Estimation." Sensors 18, no. 10 (September 25, 2018): 3226. http://dx.doi.org/10.3390/s18103226.
Повний текст джерелаKłosowski, Grzegorz, Anna Hoła, Tomasz Rymarczyk, Mariusz Mazurek, Konrad Niderla, and Magdalena Rzemieniak. "Using Machine Learning in Electrical Tomography for Building Energy Efficiency through Moisture Detection." Energies 16, no. 4 (February 11, 2023): 1818. http://dx.doi.org/10.3390/en16041818.
Повний текст джерелаNguyen, 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.
Повний текст джерелаBilgera, Christian, Akifumi Yamamoto, Maki Sawano, Haruka Matsukura, and Hiroshi Ishida. "Application of Convolutional Long Short-Term Memory Neural Networks to Signals Collected from a Sensor Network for Autonomous Gas Source Localization in Outdoor Environments." Sensors 18, no. 12 (December 18, 2018): 4484. http://dx.doi.org/10.3390/s18124484.
Повний текст джерелаYu, Dian, and Shouqian Sun. "A Systematic Exploration of Deep Neural Networks for EDA-Based Emotion Recognition." Information 11, no. 4 (April 15, 2020): 212. http://dx.doi.org/10.3390/info11040212.
Повний текст джерелаKumar, M. Pranay. "Image Captioning Generator Using CNN and LSTM." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 2847–51. http://dx.doi.org/10.22214/ijraset.2022.44502.
Повний текст джерелаBen Ismail, Mohamed Maher. "Insult detection using a partitional CNN-LSTM model." Computer Science and Information Technologies 1, no. 2 (July 1, 2020): 84–92. http://dx.doi.org/10.11591/csit.v1i2.p84-92.
Повний текст джерелаHe, Yijuan, Jidong Lv, Hongjie Liu, and Tao Tang. "Toward the Trajectory Predictor for Automatic Train Operation System Using CNN–LSTM Network." Actuators 11, no. 9 (August 31, 2022): 247. http://dx.doi.org/10.3390/act11090247.
Повний текст джерелаMing, Ye, Hu Qian, and Liu Guangyuan. "CNN-LSTM Facial Expression Recognition Method Fused with Two-Layer Attention Mechanism." Computational Intelligence and Neuroscience 2022 (October 13, 2022): 1–9. http://dx.doi.org/10.1155/2022/7450637.
Повний текст джерелаAlamri, Nawaf Mohammad H., Michael Packianather, and Samuel Bigot. "Optimizing the Parameters of Long Short-Term Memory Networks Using the Bees Algorithm." Applied Sciences 13, no. 4 (February 16, 2023): 2536. http://dx.doi.org/10.3390/app13042536.
Повний текст джерелаK A, Shirien, Neethu George, and Surekha Mariam Varghese. "Descriptive Answer Script Grading System using CNN-BiLSTM Network." International Journal of Recent Technology and Engineering 9, no. 5 (January 30, 2021): 139–44. http://dx.doi.org/10.35940/ijrte.e5212.019521.
Повний текст джерелаShen, Qianqiao, Guiyong Wang, Yuhua Wang, Boshun Zeng, Xuan Yu, and Shuchao He. "Prediction Model for Transient NOx Emission of Diesel Engine Based on CNN-LSTM Network." Energies 16, no. 14 (July 13, 2023): 5347. http://dx.doi.org/10.3390/en16145347.
Повний текст джерелаYao, Ruizhe, Ning Wang, Zhihui Liu, Peng Chen, and Xianjun Sheng. "Intrusion Detection System in the Advanced Metering Infrastructure: A Cross-Layer Feature-Fusion CNN-LSTM-Based Approach." Sensors 21, no. 2 (January 18, 2021): 626. http://dx.doi.org/10.3390/s21020626.
Повний текст джерелаZhang, Chun-Xiang, Shu-Yang Pang, Xue-Yao Gao, Jia-Qi Lu, and Bo Yu. "Attention Neural Network for Biomedical Word Sense Disambiguation." Discrete Dynamics in Nature and Society 2022 (January 10, 2022): 1–14. http://dx.doi.org/10.1155/2022/6182058.
Повний текст джерелаWei, Jun, Fan Yang, Xiao-Chen Ren, and Silin Zou. "A Short-Term Prediction Model of PM2.5 Concentration Based on Deep Learning and Mode Decomposition Methods." Applied Sciences 11, no. 15 (July 27, 2021): 6915. http://dx.doi.org/10.3390/app11156915.
Повний текст джерелаAlshingiti, Zainab, Rabeah Alaqel, Jalal Al-Muhtadi, Qazi Emad Ul Haq, Kashif Saleem, and Muhammad Hamza Faheem. "A Deep Learning-Based Phishing Detection System Using CNN, LSTM, and LSTM-CNN." Electronics 12, no. 1 (January 3, 2023): 232. http://dx.doi.org/10.3390/electronics12010232.
Повний текст джерелаMou, Hanlin, and Junsheng Yu. "CNN-LSTM Prediction Method for Blood Pressure Based on Pulse Wave." Electronics 10, no. 14 (July 13, 2021): 1664. http://dx.doi.org/10.3390/electronics10141664.
Повний текст джерелаWang, Changyuan, Ting Yan, and Hongbo Jia. "Spatial-Temporal Feature Representation Learning for Facial Fatigue Detection." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 12 (August 27, 2018): 1856018. http://dx.doi.org/10.1142/s0218001418560189.
Повний текст джерелаSun, Jiaqi, Jiarong Wang, Zhicheng Hao, Ming Zhu, Haijiang Sun, Ming Wei, and Kun Dong. "AC-LSTM: Anomaly State Perception of Infrared Point Targets Based on CNN+LSTM." Remote Sensing 14, no. 13 (July 4, 2022): 3221. http://dx.doi.org/10.3390/rs14133221.
Повний текст джерелаAshraf, Mohsin, Fazeel Abid, Ikram Ud Din, Jawad Rasheed, Mirsat Yesiltepe, Sook Fern Yeo, and Merve T. Ersoy. "A Hybrid CNN and RNN Variant Model for Music Classification." Applied Sciences 13, no. 3 (January 22, 2023): 1476. http://dx.doi.org/10.3390/app13031476.
Повний текст джерелаAlam, Muhammad S., AKM B. Hossain, and Farhan B. Mohamed. "Performance Evaluation of Recurrent Neural Networks Applied to Indoor Camera Localization." International Journal of Emerging Technology and Advanced Engineering 12, no. 8 (August 2, 2022): 116–24. http://dx.doi.org/10.46338/ijetae0822_15.
Повний текст джерелаKim, Tae-Young, and Sung-Bae Cho. "Predicting residential energy consumption using CNN-LSTM neural networks." Energy 182 (September 2019): 72–81. http://dx.doi.org/10.1016/j.energy.2019.05.230.
Повний текст джерелаLi, Shuyan, Zhixiang Chen, Xiu Li, Jiwen Lu, and Jie Zhou. "Unsupervised Variational Video Hashing With 1D-CNN-LSTM Networks." IEEE Transactions on Multimedia 22, no. 6 (June 2020): 1542–54. http://dx.doi.org/10.1109/tmm.2019.2946096.
Повний текст джерелаSperandio Nascimento, Erick Giovani, Júnia Ortiz, Adhvan Novais Furtado, and Diego Frias. "Using discrete wavelet transform for optimizing COVID-19 new cases and deaths prediction worldwide with deep neural networks." PLOS ONE 18, no. 4 (April 6, 2023): e0282621. http://dx.doi.org/10.1371/journal.pone.0282621.
Повний текст джерелаZhang, Yilin. "Short-Term Power Load Forecasting Based on SAPSO-CNN-LSTM Model considering Autocorrelated Errors." Mathematical Problems in Engineering 2022 (May 14, 2022): 1–10. http://dx.doi.org/10.1155/2022/2871889.
Повний текст джерелаZhang, Chen, Qingxu Li, and Xue Cheng. "Text Sentiment Classification Based on Feature Fusion." Revue d'Intelligence Artificielle 34, no. 4 (September 30, 2020): 515–20. http://dx.doi.org/10.18280/ria.340418.
Повний текст джерелаAlam, Md Shahinur, Ki-Chul Kwon, Shariar Md Imtiaz, Md Biddut Hossain, Bong-Gyun Kang, and Nam Kim. "TARNet: An Efficient and Lightweight Trajectory-Based Air-Writing Recognition Model Using a CNN and LSTM Network." Human Behavior and Emerging Technologies 2022 (September 24, 2022): 1–13. http://dx.doi.org/10.1155/2022/6063779.
Повний текст джерелаBarua, Arnab, Daniel Fuller, Sumayyah Musa, and Xianta Jiang. "Exploring Orientation Invariant Heuristic Features with Variant Window Length of 1D-CNN-LSTM in Human Activity Recognition." Biosensors 12, no. 7 (July 21, 2022): 549. http://dx.doi.org/10.3390/bios12070549.
Повний текст джерелаDu, Wenjun, Bo Sun, Jiating Kuai, Jiemin Xie, Jie Yu, and Tuo Sun. "Highway Travel Time Prediction of Segments Based on ANPR Data considering Traffic Diversion." Journal of Advanced Transportation 2021 (July 9, 2021): 1–16. http://dx.doi.org/10.1155/2021/9512501.
Повний текст джерелаJing, Xin, Jungang Luo, Shangyao Zhang, and Na Wei. "Runoff forecasting model based on variational mode decomposition and artificial neural networks." Mathematical Biosciences and Engineering 19, no. 2 (2021): 1633–48. http://dx.doi.org/10.3934/mbe.2022076.
Повний текст джерелаLiu, Kun, Yong Liu, Shuo Ji, Chi Gao, Shizhong Zhang, and Jun Fu. "A Novel Gait Phase Recognition Method Based on DPF-LSTM-CNN Using Wearable Inertial Sensors." Sensors 23, no. 13 (June 26, 2023): 5905. http://dx.doi.org/10.3390/s23135905.
Повний текст джерелаArif, Sheeraz, Jing Wang, Tehseen Ul Hassan, and Zesong Fei. "3D-CNN-Based Fused Feature Maps with LSTM Applied to Action Recognition." Future Internet 11, no. 2 (February 13, 2019): 42. http://dx.doi.org/10.3390/fi11020042.
Повний текст джерелаSun, Tuo, Chenwei Yang, Ke Han, Wanjing Ma, and Fan Zhang. "Bidirectional Spatial–Temporal Network for Traffic Prediction with Multisource Data." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 8 (July 5, 2020): 78–89. http://dx.doi.org/10.1177/0361198120927393.
Повний текст джерелаLivieris, Ioannis E., Niki Kiriakidou, Stavros Stavroyiannis, and Panagiotis Pintelas. "An Advanced CNN-LSTM Model for Cryptocurrency Forecasting." Electronics 10, no. 3 (January 26, 2021): 287. http://dx.doi.org/10.3390/electronics10030287.
Повний текст джерелаZhou, Xiu, Xutao Wu, Pei Ding, Xiuguang Li, Ninghui He, Guozhi Zhang, and Xiaoxing Zhang. "Research on Transformer Partial Discharge UHF Pattern Recognition Based on Cnn-lstm." Energies 13, no. 1 (December 20, 2019): 61. http://dx.doi.org/10.3390/en13010061.
Повний текст джерелаDu, Shaohui, Zhenghan Chen, Haoyan Wu, Yihong Tang, and YuanQing Li. "Image Recommendation Algorithm Combined with Deep Neural Network Designed for Social Networks." Complexity 2021 (July 2, 2021): 1–9. http://dx.doi.org/10.1155/2021/5196190.
Повний текст джерелаLu, Wenxing, Haidong Rui, Changyong Liang, Li Jiang, Shuping Zhao, and Keqing Li. "A Method Based on GA-CNN-LSTM for Daily Tourist Flow Prediction at Scenic Spots." Entropy 22, no. 3 (February 25, 2020): 261. http://dx.doi.org/10.3390/e22030261.
Повний текст джерелаChen, Ningyan. "Visual recognition and prediction analysis of China’s real estate index and stock trend based on CNN-LSTM algorithm optimized by neural networks." PLOS ONE 18, no. 2 (February 24, 2023): e0282159. http://dx.doi.org/10.1371/journal.pone.0282159.
Повний текст джерелаChuang, Chia-Chun, Chien-Ching Lee, Chia-Hong Yeng, Edmund-Cheung So, and Yeou-Jiunn Chen. "Attention Mechanism-Based Convolutional Long Short-Term Memory Neural Networks to Electrocardiogram-Based Blood Pressure Estimation." Applied Sciences 11, no. 24 (December 17, 2021): 12019. http://dx.doi.org/10.3390/app112412019.
Повний текст джерелаLu, Yi-Xiang, Xiao-Bo Jin, Dong-Jie Liu, Xin-Chang Zhang, and Guang-Gang Geng. "Anomaly Detection Using Multiscale C-LSTM for Univariate Time-Series." Security and Communication Networks 2023 (January 23, 2023): 1–12. http://dx.doi.org/10.1155/2023/6597623.
Повний текст джерелаFu, Lei, Qizhi Tang, Peng Gao, Jingzhou Xin, and Jianting Zhou. "Damage Identification of Long-Span Bridges Using the Hybrid of Convolutional Neural Network and Long Short-Term Memory Network." Algorithms 14, no. 6 (June 8, 2021): 180. http://dx.doi.org/10.3390/a14060180.
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