| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Samuel Terra Vieira, Renata Lopes Rosa, Demóstenes Zegarra Rodríguez, Miguel Arjona Ramírez, Muhammad Saadi, Lunchakorn Wuttisittikulki. Q-Meter: Quality Monitoring System for Telecommunication Services Based on Sentiment Analysis Using Deep Learning. Sensors (Basel, Switzerland). vol 21. issue 5. 2021-04-06. PMID:33800230. |
experimental results demonstrated that sentiment analysis based on a convolutional neural network (cnn) and a bidirectional long short-term memory (blstm)-recurrent neural network (rnn) with the soft-root-sign (srs) activation function presented a precision of 97% for weak signal topic classification. |
2021-04-06 |
2023-08-13 |
Not clear |
| Mihail Burduja, Radu Tudor Ionescu, Nicolae Verg. Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks. Sensors (Basel, Switzerland). vol 20. issue 19. 2021-04-02. PMID:33019508. |
the proposed system is based on a lightweight deep neural network architecture composed of a convolutional neural network (cnn) that takes as input individual ct slices, and a long short-term memory (lstm) network that takes as input multiple feature embeddings provided by the cnn. |
2021-04-02 |
2023-08-13 |
human |
| Stephanie Baker, Wei Xiang, Ian Atkinso. Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach. Scientific reports. vol 10. issue 1. 2021-03-29. PMID:33277530. |
we develop a hybrid neural network model that combines convolutional (cnn) layers with bidirectional long short-term memory (bilstm) to predict mortality from statistics describing the variation of heart rate, blood pressure, respiratory rate, blood oxygen levels, and temperature. |
2021-03-29 |
2023-08-13 |
Not clear |
| Muhammad Najam Dar, Muhammad Usman Akram, Sajid Gul Khawaja, Amit N Pujar. CNN and LSTM-Based Emotion Charting Using Physiological Signals. Sensors (Basel, Switzerland). vol 20. issue 16. 2021-03-25. PMID:32823807. |
to overcome these challenges, we propose a computational framework of 2d convolutional neural network (cnn) architecture for the arrangement of 14 channels of eeg, and a combination of long short-term memory (lstm) and 1d-cnn architecture for ecg and gsr. |
2021-03-25 |
2023-08-13 |
Not clear |
| Keisuke Ota, Yousuke Nishiura, Saki Ishihara, Hihoko Adachi, Takehisa Yamamoto, Takayuki Haman. Evaluation of Hemodialysis Arteriovenous Bruit by Deep Learning. Sensors (Basel, Switzerland). vol 20. issue 17. 2021-03-25. PMID:32867220. |
the extracted single-heartbeat arteriovenous fistula sounds were sent to a spectrogram and scored using a cnn learning model with bidirectional long short-term memory, in which the degree of arteriovenous fistula stenosis was assigned to one of five sound types (i.e., normal, hard, high, intermittent, and whistling). |
2021-03-25 |
2023-08-13 |
Not clear |
| Mohamed ElSaadani, Emad Habib, Ahmed M Abdelhameed, Magdy Bayoum. Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations. Frontiers in artificial intelligence. vol 4. 2021-03-23. PMID:33748748. |
for example, the convolutional neural network (cnn) algorithm is well suited for capturing and learning spatial patterns, while the long short-term memory (lstm) algorithm is designed to utilize time-series information and to learn from past observations. |
2021-03-23 |
2023-08-13 |
Not clear |
| Kamilya Smagulova, Olga Krestinskaya, Alex Jame. Who is the Winner? Memristive-CMOS Hybrid Modules: CNN-LSTM Versus HTM. IEEE transactions on biomedical circuits and systems. vol 14. issue 2. 2021-03-15. PMID:31794405. |
the main contribution of this work is showing that convolutional neural network (cnn) in combination with long short term memory (lstm) can be a good alternative for implementing the hierarchy, modularity and sparsity of information processing. |
2021-03-15 |
2023-08-13 |
Not clear |
| Ying Wei, Jun Zhou, Yin Wang, Yinggang Liu, Qingsong Liu, Jiansheng Luo, Chao Wang, Fengbo Ren, Li Huan. A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications. IEEE transactions on biomedical circuits and systems. vol 14. issue 2. 2021-03-15. PMID:32078560. |
for algorithm design, various widely used biomedical signal classification algorithms have been discussed including support vector machine (svm), back propagation neural network (bpnn), convolutional neural networks (cnn), probabilistic neural networks (pnn), recurrent neural networks (rnn), short-term memory network (lstm), fuzzy neural network and etc. |
2021-03-15 |
2023-08-13 |
Not clear |
| Ching-Han Chen, Chien-Chun Wang, Yan-Zhen Che. Intelligent Brushing Monitoring Using a Smart Toothbrush with Recurrent Probabilistic Neural Network. Sensors (Basel, Switzerland). vol 21. issue 4. 2021-03-05. PMID:33578684. |
compared to conventional deep learning models, the recognition accuracy of rpnn is 99.08% in our experiments, which is 16.2% higher than that of the convolutional neural network (cnn) and 21.21% higher than the long short-term memory (lstm) model. |
2021-03-05 |
2023-08-13 |
Not clear |
| Siddharth Kannan, Gaurav Yengera, Didier Mutter, Jacques Marescaux, Nicolas Pado. Future-State Predicting LSTM for Early Surgery Type Recognition. IEEE transactions on medical imaging. vol 39. issue 3. 2021-03-04. PMID:31352339. |
to capture the spatio-temporal dependencies in these videos, we choose as our model a combination of a convolutional neural network (cnn) and long short-term memory (lstm) network. |
2021-03-04 |
2023-08-13 |
Not clear |
| Junhua Ye, Xin Li, Xiangdong Zhang, Qin Zhang, Wu Che. Deep Learning-Based Human Activity Real-Time Recognition for Pedestrian Navigation. Sensors (Basel, Switzerland). vol 20. issue 9. 2021-03-04. PMID:32366055. |
in the procedure of recognition, we designed and trained deep learning models using lstm (long short-term memory) and cnn (convolutional neural network) networks based on tensorflow framework. |
2021-03-04 |
2023-08-13 |
human |
| Faisal Mehmood Butt, Lal Hussain, Anzar Mahmood, Kashif Javed Lon. Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands. Mathematical biosciences and engineering : MBE. vol 18. issue 1. 2021-02-18. PMID:33525099. |
to extract the local trends and to capture the same patterns of short, and medium forecasting time series, we proposed long short-term memory (lstm), multilayer perceptron, and convolutional neural network (cnn) to learn the relationship in the time series. |
2021-02-18 |
2023-08-13 |
Not clear |
| Seongyoep Jeong, Inyoung Park, Hyun Soo Kim, Chul Han Song, Hong Kook Ki. Temperature Prediction Based on Bidirectional Long Short-Term Memory and Convolutional Neural Network Combining Observed and Numerical Forecast Data. Sensors (Basel, Switzerland). vol 21. issue 3. 2021-02-15. PMID:33572653. |
to accommodate such different types of data into a single model, a bidirectional long short-term memory (blstm) model and a convolutional neural network (cnn) model are chosen to represent the features from the time-series observed data and the rdaps image data. |
2021-02-15 |
2023-08-13 |
Not clear |
| Zhe Liu, Yingli Gong, Yihang Bao, Yuanzhao Guo, Han Wang, Guan Ning Li. TMPSS: A Deep Learning-Based Predictor for Secondary Structure and Topology Structure Prediction of Alpha-Helical Transmembrane Proteins. Frontiers in bioengineering and biotechnology. vol 8. 2021-02-12. PMID:33569377. |
tmpss applied a convolutional neural network (cnn), combined with an attention-enhanced bidirectional long short-term memory (bilstm) network, to extract the local contexts and long-distance interdependencies from primary sequences. |
2021-02-12 |
2023-08-13 |
Not clear |
| Koppaka Ganesh Sai Apuroop, Anh Vu Le, Mohan Rajesh Elara, Bing J She. Reinforcement Learning-Based Complete Area Coverage Path Planning for a Modified hTrihex Robot. Sensors (Basel, Switzerland). vol 21. issue 4. 2021-02-10. PMID:33557225. |
in this regard, a convolutional neural network (cnn) with long short term memory (lstm) layer was trained using the actor-critic experience replay (acer) reinforcement learning algorithm. |
2021-02-10 |
2023-08-13 |
Not clear |
| Yen-Hung Chen, Yuan-Cheng Lai, Pi-Tzong Jan, Ting-Yi Tsa. A Spatiotemporal-Oriented Deep Ensemble Learning Model to Defend Link Flooding Attacks in IoT Network. Sensors (Basel, Switzerland). vol 21. issue 4. 2021-02-08. PMID:33546204. |
(3) methods: this study designs a deep ensemble learning model (stacking-based integrated convolutional neural network-long short term memory model, scl) to defend against lfa: (a) combining continuous network status as an input to represent "continuous/combination attacking action" and to help cnn operation to extract features of spatiotemporal attack pattern; (b) applying lstm to periodically review the current evolved lfa patterns and drop the obsolete ones to ensure decision accuracy and confidence; (c) stacking system detector and lfa mitigator module instead of only one module to couple with lfa detection and mediation at the same time. |
2021-02-08 |
2023-08-13 |
Not clear |
| Meriem Zerkouk, Belkacem Chikhaou. Spatio-Temporal Abnormal Behavior Prediction in Elderly Persons Using Deep Learning Models. Sensors (Basel, Switzerland). vol 20. issue 8. 2021-02-04. PMID:32326349. |
in this paper, we investigate a variety of deep learning models such as long short term memory (lstm), convolutional neural network (cnn), cnn-lstm and autoencoder-cnn-lstm for identifying and accurately predicting the abnormal behaviors of elderly people. |
2021-02-04 |
2023-08-13 |
Not clear |
| Ahmed Sedik, Mohamed Hammad, Fathi E Abd El-Samie, Brij B Gupta, Ahmed A Abd El-Lati. Efficient deep learning approach for augmented detection of Coronavirus disease. Neural computing & applications. 2021-01-26. PMID:33487885. |
the proposed deep learning modalities are based on convolutional neural network (cnn) and convolutional long short-term memory (convlstm). |
2021-01-26 |
2023-08-13 |
Not clear |
| Oh Shu Lih, V Jahmunah, Tan Ru San, Edward J Ciaccio, Toshitaka Yamakawa, Masayuki Tanabe, Makiko Kobayashi, Oliver Faust, U Rajendra Achary. Comprehensive electrocardiographic diagnosis based on deep learning. Artificial intelligence in medicine. vol 103. 2021-01-25. PMID:32143796. |
the convolutional neural network (cnn), followed by combined cnn and long short-term memory (lstm) models, appear to be the most useful architectures for classification. |
2021-01-25 |
2023-08-13 |
Not clear |
| Ruizhe Yao, Ning Wang, Zhihui Liu, Peng Chen, Xianjun Shen. Intrusion Detection System in the Advanced Metering Infrastructure: A Cross-Layer Feature-Fusion CNN-LSTM-Based Approach. Sensors (Basel, Switzerland). vol 21. issue 2. 2021-01-22. PMID:33477451. |
to solve these problems, an ami intrusion detection model based on the cross-layer feature fusion of a convolutional neural networks (cnn) and long short-term memory (lstm) networks is proposed in the present work. |
2021-01-22 |
2023-08-13 |
Not clear |