| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Junseo Ko, Jinyoung Han, Jeewoo Yoon, Ji In Park, Joon Seo Hwang, Jeong Mo Han, Kyu Hyung Park, Daniel Duck-Jin Hwan. Assessing central serous chorioretinopathy with deep learning and multiple optical coherence tomography images. Scientific reports. vol 12. issue 1. 2022-02-04. PMID:35115577. |
compared to other end-to-end models, for example, a 3d convolutional neural network (cnn) model and a cnn-long short-term memory (cnn-lstm) model, the proposed system showed more than 10% higher accuracy. |
2022-02-04 |
2023-08-13 |
human |
| Fatma Patlar Akbulu. Hybrid deep convolutional model-based emotion recognition using multiple physiological signals. Computer methods in biomechanics and biomedical engineering. 2022-02-02. PMID:35107402. |
the proposed approach implements several learning algorithms such as convolutional neural network (cnn), long short-term memory (lstm), recurrent neural network (rnn), and several other shallow methods on the sensor input to handle the requirements for the traditional feature extraction process. |
2022-02-02 |
2023-08-13 |
human |
| Ping Chen, JianYi Zhong, YueChao Zh. Intelligent Question Answering System by Deep Convolutional Neural Network in Finance and Economics Teaching. Computational intelligence and neuroscience. vol 2022. 2022-01-31. PMID:35096043. |
on this basis, deep learning algorithms are introduced, the long short-term memory (lstm) neural network and convolutional neural network (cnn) are combined, and a q&a system by long short-term memory-convolutional neural network (lstm-cnn) is proposed, the gated recurrent unit (gru) attention mechanism is introduced, and the algorithm is optimized. |
2022-01-31 |
2023-08-13 |
Not clear |
| Syeda Fatima Aijaz, Saad Jawaid Khan, Fahad Azim, Choudhary Sobhan Shakeel, Umer Hassa. Deep Learning Application for Effective Classification of Different Types of Psoriasis. Journal of healthcare engineering. vol 2022. 2022-01-25. PMID:35075392. |
two deep learning algorithms of convolutional neural network (cnn) and long short-term memory (lstm) were applied with the classification models being trained with 80% of the images. |
2022-01-25 |
2023-08-13 |
Not clear |
| Bor-Jiunn Hwang, Hui-Hui Chen, Chaur-Heh Hsieh, Deng-Yu Huan. Gaze Tracking Based on Concatenating Spatial-Temporal Features. Sensors (Basel, Switzerland). vol 22. issue 2. 2022-01-22. PMID:35062502. |
to be able to capture spatial and temporal features at the same time, the convolutional neural network (cnn) and long short-term memory (lstm) network are introduced to build a training model. |
2022-01-22 |
2023-08-13 |
Not clear |
| Hanqing Wang, Xiaoyuan Wang, Junyan Han, Hui Xiang, Hao Li, Yang Zhang, Shangqing L. A Recognition Method of Aggressive Driving Behavior Based on Ensemble Learning. Sensors (Basel, Switzerland). vol 22. issue 2. 2022-01-22. PMID:35062603. |
second, three deep learning methods, including convolutional neural networks (cnn), long short-term memory (lstm), and gated recurrent unit (gru), are employed to build the base classifiers for the class balance datasets. |
2022-01-22 |
2023-08-13 |
Not clear |
| Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M Iftekharuddin, Md Monibor Rahman, Anna S Shabalin. Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory. Frontiers in artificial intelligence. vol 4. 2022-01-20. PMID:35047766. |
in particular, the performance of rnn models incorporating long short-term memory (lstm) are analyzed along with the cnn performance. |
2022-01-20 |
2023-08-13 |
human |
| Eman Shalaby, Nada ElShennawy, Amany Sarha. Utilizing deep learning models in CSI-based human activity recognition. Neural computing & applications. 2022-01-12. PMID:35017796. |
four deep learning models are presented in this paper, namely: a convolution neural network (cnn) with a gated recurrent unit (gru); a cnn with a gru and attention; a cnn with a gru and a second cnn, and a cnn with long short-term memory (lstm) and a second cnn. |
2022-01-12 |
2023-08-13 |
human |
| Manas Bazarbaev, Tserenpurev Chuluunsaikhan, Hyoseok Oh, Ga-Ae Ryu, Aziz Nasridinov, Kwan-Hee Yo. Generation of Time-Series Working Patterns for Manufacturing High-Quality Products through Auxiliary Classifier Generative Adversarial Network. Sensors (Basel, Switzerland). vol 22. issue 1. 2022-01-11. PMID:35009572. |
specifically, the proposed model results were compared with those of other deep learning models: multilayer perceptron (mlp), convolutional neural network (cnn), long short-term memory (lstm), and gated recurrent unit (gru). |
2022-01-11 |
2023-08-13 |
Not clear |
| Junhyuk Kang, Jieun Shin, Jaewon Shin, Daeho Lee, Ahyoung Cho. Robust Human Activity Recognition by Integrating Image and Accelerometer Sensor Data Using Deep Fusion Network. Sensors (Basel, Switzerland). vol 22. issue 1. 2022-01-11. PMID:35009717. |
for accelerometer data, we use a convolutional neural network (cnn) and convolutional block attention module models (cbam), and apply bidirectional long short-term memory and a residual neural network. |
2022-01-11 |
2023-08-13 |
human |
| Imran Ullah Khan, Sitara Afzal, Jong Weon Le. Human Activity Recognition via Hybrid Deep Learning Based Model. Sensors (Basel, Switzerland). vol 22. issue 1. 2022-01-11. PMID:35009865. |
considering these limitations, we develop a hybrid model by incorporating convolutional neural network (cnn) and long short-term memory (lstm) for activity recognition where cnn is used for spatial features extraction and lstm network is utilized for learning temporal information. |
2022-01-11 |
2023-08-13 |
human |
| Theyazn H H Aldhyani, Hasan Alkahtan. Attacks to Automatous Vehicles: A Deep Learning Algorithm for Cybersecurity. Sensors (Basel, Switzerland). vol 22. issue 1. 2022-01-11. PMID:35009899. |
this dataset was processed by using the convolution neural network (cnn) and a hybrid network combining cnn and long short-term memory (cnn-lstm) models to identify attack messages. |
2022-01-11 |
2023-08-13 |
Not clear |
| Zenghui Wang, Jun Zhang, Xiaochu Zhang, Peng Chen, Bing Wan. Transformer Model for Functional Near-Infrared Spectroscopy Classification. IEEE journal of biomedical and health informatics. vol PP. 2022-01-05. PMID:34986110. |
compared with traditional machine learning classifiers, convolutional neural network (cnn), and long short-term memory (lstm), the proposed models obtain the best accuracy on three open-access datasets. |
2022-01-05 |
2023-08-13 |
human |
| Binayak Bhandar. Comparative Study of Popular Deep Learning Models for Machining Roughness Classification Using Sound and Force Signals. Micromachines. vol 12. issue 12. 2021-12-24. PMID:34945334. |
the dl architectures considered in this study include multi-layer perceptron (mlp), convolution neural network (cnn), long short-term memory (lstm), and transformer. |
2021-12-24 |
2023-08-13 |
Not clear |
| Ahmed Bahaa Farid, Enas Mohamed Fathy, Ahmed Sharaf Eldin, Laila A Abd-Elmegi. Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM). PeerJ. Computer science. vol 7. 2021-12-13. PMID:34901421. |
software defect prediction using hybrid model (cbil) of convolutional neural network (cnn) and bidirectional long short-term memory (bi-lstm). |
2021-12-13 |
2023-08-13 |
Not clear |
| Shuo Liu, Jing Han, Estela Laporta Puyal, Spyridon Kontaxis, Shaoxiong Sun, Patrick Locatelli, Judith Dineley, Florian B Pokorny, Gloria Dalla Costa, Letizia Leocani, Ana Isabel Guerrero, Carlos Nos, Ana Zabalza, Per Soelberg Sørensen, Mathias Buron, Melinda Magyari, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Amos A Folarin, Richard Jb Dobson, Raquel Bailón, Srinivasan Vairavan, Nicholas Cummins, Vaibhav A Narayan, Matthew Hotopf, Giancarlo Comi, Björn Schuller, Radar-Cns Consortiu. Fitbeat: COVID-19 estimation based on wristband heart rate using a contrastive convolutional auto-encoder. Pattern recognition. vol 123. 2021-12-11. PMID:34720200. |
the contrastive cae outperforms a conventional convolutional neural network (cnn), a long short-term memory (lstm) model, and a convolutional auto-encoder without contrastive loss (cae). |
2021-12-11 |
2023-08-13 |
human |
| Jingjuan Qiao, Jiabei Tang, Jiajia Yang, Minpeng Xu, Dong Min. Basic Graphic Shape Decoding for EEG-based Brain-Computer Interfaces. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2021. 2021-12-11. PMID:34891414. |
convolutional neural network (cnn) combined with long short-term memory (lstm) was employed to decode the corresponding eeg signals. |
2021-12-11 |
2023-08-13 |
human |
| Yikai Yang, Nhan Duy Truong, Christina Maher, Armin Nikpour, Omid Kavehe. A comparative study of AI systems for epileptic seizure recognition based on EEG or ECG. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2021. 2021-12-11. PMID:34891722. |
in this work, we implement an ecg-specific convolutional neural network (cnn) model with residual layers and an eeg-specific convolutional long short-term memory (convlstm) model. |
2021-12-11 |
2023-08-13 |
Not clear |
| Caleb J Thomson, Gregory A Clark, Jacob A Georg. A Recurrent Neural Network Provides Stable Across-Day Prosthetic Control for a Human Amputee with Implanted Intramuscular Electromyographic Recording Leads. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2021. 2021-12-11. PMID:34892525. |
convolutional neural networks (cnn) and recurrent long short-term memory (lstm) networks have shown promise in extracting high-degree-of-freedom motor intent from myoelectric signals, thereby providing more intuitive and dexterous prosthetic control. |
2021-12-11 |
2023-08-13 |
human |
| Luz Santamaria-Granados, Juan Francisco Mendoza-Moreno, Angela Chantre-Astaiza, Mario Munoz-Organero, Gustavo Ramirez-Gonzale. Tourist Experiences Recommender System Based on Emotion Recognition with Wearable Data. Sensors (Basel, Switzerland). vol 21. issue 23. 2021-12-10. PMID:34883853. |
among the different algorithms tested for er, the hybrid model of convolutional neural networks (cnn) and long short-term memory (lstm) networks had promising results. |
2021-12-10 |
2023-08-13 |
Not clear |