Статті в журналах з теми "HYBRID CNN-RNN MODEL"
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Zaheer, Shahzad, Nadeem Anjum, Saddam Hussain, Abeer D. Algarni, Jawaid Iqbal, Sami Bourouis, and Syed Sajid Ullah. "A Multi Parameter Forecasting for Stock Time Series Data Using LSTM and Deep Learning Model." Mathematics 11, no. 3 (January 22, 2023): 590. http://dx.doi.org/10.3390/math11030590.
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 джерелаKrishnan, V. Gokula, M. V. Vijaya Saradhi, T. A. Mohana Prakash, K. Gokul Kannan, and AG Noorul Julaiha. "Development of Deep Learning based Intelligent Approach for Credit Card Fraud Detection." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 12 (December 31, 2022): 133–39. http://dx.doi.org/10.17762/ijritcc.v10i12.5894.
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 джерелаBehera, Bibhuti Bhusana, Binod Kumar Pattanayak, and Rajani Kanta Mohanty. "Deep Ensemble Model for Detecting Attacks in Industrial IoT." International Journal of Information Security and Privacy 16, no. 1 (January 1, 2022): 1–29. http://dx.doi.org/10.4018/ijisp.311467.
Повний текст джерелаCheng, 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.
Повний текст джерелаPawar, Mahendra Eknath, Rais Allauddin Mulla, Sanjivani H. Kulkarni, Sajeeda Shikalgar, Harikrishna B. Jethva, and Gunvant A. Patel. "A Novel Hybrid AI Federated ML/DL Models for Classification of Soil Components." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 1s (December 10, 2022): 190–99. http://dx.doi.org/10.17762/ijritcc.v10i1s.5823.
Повний текст джерелаUTKU, Anıl. "Kentsel Trafik Tahminine Yönelik Derin Öğrenme Tabanlı Verimli Bir Hibrit Model." Bilişim Teknolojileri Dergisi 16, no. 2 (April 30, 2023): 107–17. http://dx.doi.org/10.17671/gazibtd.1167140.
Повний текст джерелаLiang, Youzhi, Wen Liang, and Jianguo Jia. "Structural Vibration Signal Denoising Using Stacking Ensemble of Hybrid CNN-RNN." Advances in Artificial Intelligence and Machine Learning 03, no. 02 (2023): 1110–22. http://dx.doi.org/10.54364/aaiml.2023.1165.
Повний текст джерелаZhang, Langlang, Jun Xie, Xinxiu Liu, Wenbo Zhang, and Pan Geng. "Research on water quality prediction based on PE-CNN-GRU hybrid model." E3S Web of Conferences 393 (2023): 02014. http://dx.doi.org/10.1051/e3sconf/202339302014.
Повний текст джерелаKhamparia, Aditya, Babita Pandey, Shrasti Tiwari, Deepak Gupta, Ashish Khanna, and Joel J. P. C. Rodrigues. "An Integrated Hybrid CNN–RNN Model for Visual Description and Generation of Captions." Circuits, Systems, and Signal Processing 39, no. 2 (November 11, 2019): 776–88. http://dx.doi.org/10.1007/s00034-019-01306-8.
Повний текст джерелаUly, Novem, Hendry Hendry, and Ade Iriani. "CNN-RNN Hybrid Model for Diagnosis of COVID-19 on X-Ray Imagery." Digital Zone: Jurnal Teknologi Informasi dan Komunikasi 14, no. 1 (May 27, 2023): 57–67. http://dx.doi.org/10.31849/digitalzone.v14i1.13668.
Повний текст джерелаArshad, Muhammad Zeeshan, Ankhzaya Jamsrandorj, Jinwook Kim, and Kyung-Ryoul Mun. "Gait Events Prediction Using Hybrid CNN-RNN-Based Deep Learning Models through a Single Waist-Worn Wearable Sensor." Sensors 22, no. 21 (October 27, 2022): 8226. http://dx.doi.org/10.3390/s22218226.
Повний текст джерелаGong, Liyun, Miao Yu, Vassilis Cutsuridis, Stefanos Kollias, and Simon Pearson. "A Novel Model Fusion Approach for Greenhouse Crop Yield Prediction." Horticulturae 9, no. 1 (December 20, 2022): 5. http://dx.doi.org/10.3390/horticulturae9010005.
Повний текст джерелаKang, Taehyung, Dae Yeong Lim, Hilal Tayara, and Kil To Chong. "Forecasting of Power Demands Using Deep Learning." Applied Sciences 10, no. 20 (October 16, 2020): 7241. http://dx.doi.org/10.3390/app10207241.
Повний текст джерелаHasbullah, Sumayyah, Mohd Soperi Mohd Zahid, and Satria Mandala. "Detection of Myocardial Infarction Using Hybrid Models of Convolutional Neural Network and Recurrent Neural Network." BioMedInformatics 3, no. 2 (June 15, 2023): 478–92. http://dx.doi.org/10.3390/biomedinformatics3020033.
Повний текст джерелаRong, Guangzhi, Kaiwei Li, Yulin Su, Zhijun Tong, Xingpeng Liu, Jiquan Zhang, Yichen Zhang, and Tiantao Li. "Comparison of Tree-Structured Parzen Estimator Optimization in Three Typical Neural Network Models for Landslide Susceptibility Assessment." Remote Sensing 13, no. 22 (November 20, 2021): 4694. http://dx.doi.org/10.3390/rs13224694.
Повний текст джерелаSharma, Richa, Sudha Morwal, and Basant Agarwal. "Entity-Extraction Using Hybrid Deep-Learning Approach for Hindi text." International Journal of Cognitive Informatics and Natural Intelligence 15, no. 3 (July 2021): 1–11. http://dx.doi.org/10.4018/ijcini.20210701.oa1.
Повний текст джерелаGuo, Yanan, Xiaoqun Cao, Bainian Liu, and Kecheng Peng. "El Niño Index Prediction Using Deep Learning with Ensemble Empirical Mode Decomposition." Symmetry 12, no. 6 (June 1, 2020): 893. http://dx.doi.org/10.3390/sym12060893.
Повний текст джерелаMas-Pujol, Sergi, Esther Salamí, and Enric Pastor. "RNN-CNN Hybrid Model to Predict C-ATC CAPACITY Regulations for En-Route Traffic." Aerospace 9, no. 2 (February 10, 2022): 93. http://dx.doi.org/10.3390/aerospace9020093.
Повний текст джерелаLapa, Paulo, Mauro Castelli, Ivo Gonçalves, Evis Sala, and Leonardo Rundo. "A Hybrid End-to-End Approach Integrating Conditional Random Fields into CNNs for Prostate Cancer Detection on MRI." Applied Sciences 10, no. 1 (January 2, 2020): 338. http://dx.doi.org/10.3390/app10010338.
Повний текст джерелаBeseiso, Majdi. "Word and Character Information Aware Neural Model for Emotional Analysis." Recent Patents on Computer Science 12, no. 2 (February 25, 2019): 142–47. http://dx.doi.org/10.2174/2213275911666181119112645.
Повний текст джерелаAmer, Rusul, and Ahmed Al Tmeme. "Hybrid Deep Learning Model for Singing Voice Separation." MENDEL 27, no. 2 (December 21, 2021): 44–50. http://dx.doi.org/10.13164/mendel.2021.2.044.
Повний текст джерелаZhang, Dong, and Qichuan Tian. "A Novel Fuzzy Optimized CNN-RNN Method for Facial Expression Recognition." Elektronika ir Elektrotechnika 27, no. 5 (October 27, 2021): 67–74. http://dx.doi.org/10.5755/j02.eie.29648.
Повний текст джерелаWang, Yu, Yining Sun, Zuchang Ma, Lisheng Gao, and Yang Xu. "A Hybrid Model for Named Entity Recognition on Chinese Electronic Medical Records." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 2 (April 23, 2021): 1–12. http://dx.doi.org/10.1145/3436819.
Повний текст джерелаRoy, Bishwajit, Lokesh Malviya, Radhikesh Kumar, Sandip Mal, Amrendra Kumar, Tanmay Bhowmik, and Jong Wan Hu. "Hybrid Deep Learning Approach for Stress Detection Using Decomposed EEG Signals." Diagnostics 13, no. 11 (June 1, 2023): 1936. http://dx.doi.org/10.3390/diagnostics13111936.
Повний текст джерелаYadav, Omprakash, Rachael Dsouza, Rhea Dsouza, and Janice Jose. "Soccer Action video Classification using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 1060–63. http://dx.doi.org/10.22214/ijraset.2022.43929.
Повний текст джерелаMekruksavanich, Sakorn, and Anuchit Jitpattanakul. "Deep Convolutional Neural Network with RNNs for Complex Activity Recognition Using Wrist-Worn Wearable Sensor Data." Electronics 10, no. 14 (July 14, 2021): 1685. http://dx.doi.org/10.3390/electronics10141685.
Повний текст джерелаFarid, Ahmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin, and Laila A. Abd-Elmegid. "Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM)." PeerJ Computer Science 7 (November 16, 2021): e739. http://dx.doi.org/10.7717/peerj-cs.739.
Повний текст джерелаÇAVDAR, İsmail, and Vahid FARYAD. "New Design of a Supervised Energy Disaggregation Model Based on the Deep Neural Network for a Smart Grid." Energies 12, no. 7 (March 29, 2019): 1217. http://dx.doi.org/10.3390/en12071217.
Повний текст джерелаWEN, HAO, WENJIAN YU, YUANQING WU, SHUAI YANG, and XIAOLONG LIU. "A SCALABLE HYBRID MODEL FOR ATRIAL FIBRILLATION DETECTION." Journal of Mechanics in Medicine and Biology 21, no. 05 (April 17, 2021): 2140021. http://dx.doi.org/10.1142/s0219519421400212.
Повний текст джерелаRafi, Quazi Ghulam, Mohammed Noman, Sadia Zahin Prodhan, Sabrina Alam, and Dip Nandi. "Comparative Analysis of Three Improved Deep Learning Architectures for Music Genre Classification." International Journal of Information Technology and Computer Science 13, no. 2 (April 8, 2021): 1–14. http://dx.doi.org/10.5815/ijitcs.2021.02.01.
Повний текст джерелаDhar, Puja, Vijay Kumar Garg, and Mohammad Anisur Rahman. "Enhanced Feature Extraction-based CNN Approach for Epileptic Seizure Detection from EEG Signals." Journal of Healthcare Engineering 2022 (March 16, 2022): 1–14. http://dx.doi.org/10.1155/2022/3491828.
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 джерелаUmair, Muhammad, Muhammad Zubair, Farhan Dawood, Sarim Ashfaq, Muhammad Shahid Bhatti, Mohammad Hijji, and Abid Sohail. "A Multi-Layer Holistic Approach for Cursive Text Recognition." Applied Sciences 12, no. 24 (December 9, 2022): 12652. http://dx.doi.org/10.3390/app122412652.
Повний текст джерелаMoradzadeh, Arash, Sahar Zakeri, Waleed A. Oraibi, Behnam Mohammadi-Ivatloo, Zulkurnain Abdul-Malek, and Reza Ghorbani. "Non-Intrusive Load Monitoring of Residential Loads via Laplacian Eigenmaps and Hybrid Deep Learning Procedures." Sustainability 14, no. 22 (November 11, 2022): 14898. http://dx.doi.org/10.3390/su142214898.
Повний текст джерелаBao, Zhengyi, Jiahao Jiang, Chunxiang Zhu, and Mingyu Gao. "A New Hybrid Neural Network Method for State-of-Health Estimation of Lithium-Ion Battery." Energies 15, no. 12 (June 16, 2022): 4399. http://dx.doi.org/10.3390/en15124399.
Повний текст джерелаAlrasheedi, Abdullah, and Abdulaziz Almalaq. "Hybrid Deep Learning Applied on Saudi Smart Grids for Short-Term Load Forecasting." Mathematics 10, no. 15 (July 28, 2022): 2666. http://dx.doi.org/10.3390/math10152666.
Повний текст джерелаTran Quang, Duy, and Sang Hoon Bae. "A Hybrid Deep Convolutional Neural Network Approach for Predicting the Traffic Congestion Index." Promet - Traffic&Transportation 33, no. 3 (May 31, 2021): 373–85. http://dx.doi.org/10.7307/ptt.v33i3.3657.
Повний текст джерелаHong, Taekeun, Jin-A. Choi, Kiho Lim, and Pankoo Kim. "Enhancing Personalized Ads Using Interest Category Classification of SNS Users Based on Deep Neural Networks." Sensors 21, no. 1 (December 30, 2020): 199. http://dx.doi.org/10.3390/s21010199.
Повний текст джерелаRajagukguk, Rial A., Raden A. A. Ramadhan, and Hyun-Jin Lee. "A Review on Deep Learning Models for Forecasting Time Series Data of Solar Irradiance and Photovoltaic Power." Energies 13, no. 24 (December 15, 2020): 6623. http://dx.doi.org/10.3390/en13246623.
Повний текст джерелаSelvarani, Renjith Vijayakumar, and Paul Subha Hency Jose. "A Label-Free Marker Based Breast Cancer Detection using Hybrid Deep Learning Models and Raman Spectroscopy." Trends in Sciences 20, no. 4 (January 22, 2023): 6299. http://dx.doi.org/10.48048/tis.2023.6299.
Повний текст джерелаChung, Jaewon, and Beakcheol Jang. "Accurate prediction of electricity consumption using a hybrid CNN-LSTM model based on multivariable data." PLOS ONE 17, no. 11 (November 23, 2022): e0278071. http://dx.doi.org/10.1371/journal.pone.0278071.
Повний текст джерелаGeng, Boting. "Open Relation Extraction in Patent Claims with a Hybrid Network." Wireless Communications and Mobile Computing 2021 (April 28, 2021): 1–7. http://dx.doi.org/10.1155/2021/5547281.
Повний текст джерелаAl Duhayyim, Mesfer, Hanan Abdullah Mengash, Radwa Marzouk, Mohamed K. Nour, Hany Mahgoub, Fahd Althukair, and Abdullah Mohamed. "Hybrid Rider Optimization with Deep Learning Driven Biomedical Liver Cancer Detection and Classification." Computational Intelligence and Neuroscience 2022 (June 30, 2022): 1–11. http://dx.doi.org/10.1155/2022/6162445.
Повний текст джерелаSong, Fuquan, Heying Ding, Yongzheng Wang, Shiming Zhang, and Jinbiao Yu. "A Well Production Prediction Method of Tight Reservoirs Based on a Hybrid Neural Network." Energies 16, no. 6 (March 21, 2023): 2904. http://dx.doi.org/10.3390/en16062904.
Повний текст джерелаAltalak, Maha, Mohammad Ammad uddin, Amal Alajmi, and Alwaseemah Rizg. "Smart Agriculture Applications Using Deep Learning Technologies: A Survey." Applied Sciences 12, no. 12 (June 10, 2022): 5919. http://dx.doi.org/10.3390/app12125919.
Повний текст джерелаLee, Chien-Hsing, Phuong Nguyen Thanh, Chao-Tsung Yeh, and Ming-Yuan Cho. "Three-Phase Load Prediction-Based Hybrid Convolution Neural Network Combined Bidirectional Long Short-Term Memory in Solar Power Plant." International Transactions on Electrical Energy Systems 2022 (September 16, 2022): 1–15. http://dx.doi.org/10.1155/2022/2870668.
Повний текст джерелаJishan, Md Asifuzzaman, Khan Raqib Mahmud, Abul Kalam Al Azad, Md Shahabub Alam, and Anif Minhaz Khan. "Hybrid deep neural network for Bangla automated image descriptor." International Journal of Advances in Intelligent Informatics 6, no. 2 (July 12, 2020): 109. http://dx.doi.org/10.26555/ijain.v6i2.499.
Повний текст джерелаKhortsriwong, Nonthawat, Promphak Boonraksa, Terapong Boonraksa, Thipwan Fangsuwannarak, Asada Boonsrirat, Watcharakorn Pinthurat, and Boonruang Marungsri. "Performance of Deep Learning Techniques for Forecasting PV Power Generation: A Case Study on a 1.5 MWp Floating PV Power Plant." Energies 16, no. 5 (February 22, 2023): 2119. http://dx.doi.org/10.3390/en16052119.
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