Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…The new model mentioned in this research is a hybrid model containing convolutional neural network (CNN), stacked multi-layer long short-term memory (LSTM) and max pooling layers. …”
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Research on Personal Loan Default Risk Assessment Based on Machine Learning by Liu Guangsen

“…Among them, the Deep Neural Network has the best overall performance compared to the other three machine learning models. …”
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A LiDAR - camera fusion detection method based on weight allocation by Kang Haotian, Wang Tianshu

“…In automatic driving target detection problem, the neural network is applied to two methods, vision, and LiDAR. …”
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Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition by Zhichao Wang, Yu Jiang, Jiaxin Liu, Siyu Gong, Jian Yao, Feng Jiang

“…Aiming at the problems of traditional license plate recognition algorithms such as the low accuracy, slow speed, and the recognition rate being easily affected by the environment, a Convolutional Neural Network- (CNN-) based license plate recognition algorithm-Fast-LPRNet is proposed. …”
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Low-power artificial neuron networks with enhanced synaptic functionality using dual transistor and dual memristor. by Keerthi Nalliboyina, Sakthivel Ramachandran

“…Artificial neurons with bio-inspired firing patterns have the potential to significantly improve the performance of neural network computing. The most significant component of an artificial neuron circuit is a large amount of energy consumption. …”
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One-Shot M-Array Pattern Based on Coded Structured Light for Three-Dimensional Object Reconstruction by Xiaojun Jia, Zihao Liu

“…A deep convolution neural network (DCNN) and chain sequence features are used to accurately classify pattern elements and key points (KPs), respectively. …”
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Hierarchical Deep Learning for Bearing Fault Detection in BLDC Motors Using Time-Frequency Analysis by Ahmed K. Ali, Wathiq Rafa Abed

“…This paper presents new hierarchical image-based time-frequency convolutional neural network (HTFICNN) for sorted bearing fault detection in brushless DC (BLDC) motors. …”
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New Models for Solving Time-Varying LU Decomposition by Using ZNN Method and ZeaD Formulas by Liangjie Ming, Yunong Zhang, Jinjin Guo, Xiao Liu, Zhonghua Li

“…In this paper, by employing the Zhang neural network (ZNN) method, an effective continuous-time LU decomposition (CTLUD) model is firstly proposed, analyzed, and investigated for solving the time-varying LU decomposition problem. …”
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Optimization and Prediction of Energy Consumption, Daylighting, and Thermal Comfort of Buildings in Tropical Areas by Jianjian Zhang, Lin Ji

“…Finally, the backpropagation (BP) neural network established in this research is shown to achieve good prediction of the target value and achieves the goal of green energy-saving.…”
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Machine Learning for Ischemic Heart Disease Diagnosis Aided by Evolutionary Computing by Mohammad Alsaffar, Abdullah Alshammari, Gharbi Alshammari, Saud Aljaloud, Tariq S. Almurayziq, Fadam Muteb Abdoon, Solomon Abebaw

“…A picture database containing 92 images of electrocardiogram signals was also used in this project for the analysis of the Artificial Neural Network. After extensive research and testing by the medical community, which supported the project and provided positive feedback, a successful tool was developed. …”
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ANN Synthesis Model of Single-Feed Corner-Truncated Circularly Polarized Microstrip Antenna with an Air Gap for Wideband Applications by Zhongbao Wang, Shaojun Fang

“…A computer-aided design model based on the artificial neural network (ANN) is proposed to directly obtain patch physical dimensions of the single-feed corner-truncated circularly polarized microstrip antenna (CPMA) with an air gap for wideband applications. …”
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Used economy market insight: Sailboat industry pricing mechanism and regional effects. by Zhanni Huang, Hansheng Hu, Di Wu

“…Therefore, this article uses the random forest model and XGBoost algorithm to identify core price indicators, and uses an innovative rolling NAR dynamic neural network model to simulate and predict second-hand sailboat price data. …”
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ANN and RSM Modeling for the Synthesis of Avocado Seed Starch Combined Orange Peel Extract Antimicrobial Packaging Film by Yasin Ahmed Waday, Ermias Girma Aklilu

“…The results showed that both models performed reasonably well, but trained artificial neural networks have more modeling capability rather than the response surface method. …”
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Optimal Control of Semiactive Two-Stage Vibration Isolation Systems for Marine Engines by YuanYuan Fang

“…Taking the test results of MR damper dynamic characteristics as sample data, the forward and inverse models of the MR damper are identified by the least square method and neural network (NN) method respectively, and the identification results are applied to semiactive control of the two-stage isolation system. …”
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Multimedia Data Processing Technology and Application Based on Deep Learning by Guo Li, Wei Liu

“…Then, the related network results of deep learning (convolution network structure and countermeasure neural network structure) are put forward, and the image comparison of the activation function and the loss function of deep learning is analyzed, which provides functional algorithm support for the experimental analysis of deep learning in multimedia data processing technology. …”
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A Comparative Analysis of Data-Driven Empirical and Artificial Intelligence Models for Estimating Infiltration Rates by Mohammad Zakwan, Majid Niazkar

“…In the present paper, different data-driven models including Multiple Linear Regression (MLR), Generalized Reduced Gradient (GRG), two Artificial Intelligence (AI) techniques (Artificial Neural Network (ANN) and Multigene Genetic Programming (MGGP)), and the hybrid MGGP-GRG have been applied to estimate the infiltration rates. …”
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Distributed Adaptive Coordinated Control of Multiple Euler–Lagrange Systems considering Output Constraints and Time Delays by Hongde Qin, Xiaojia Li, Yanchao Sun

“…In order to handle uncertain problems, the neural network technique is adopted to estimate the unknown dynamics. …”
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Deep Learning Implementation Using CNN to Classify Bali God Sculpture Pictures by Ni Luh Gede Pivin Suwirmayanti, I Wayan Budi Sentana, I Ketut Gede Darma Putra, Made Sudarma, I Made Sukarsa, Komang Budiarta

“…The technique used in Deep Learning is Convolutional Neural Network (CNN). The training process is first performed to perform the classification process, and then the testing process is performed. …”
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Scholarships Determination to Talented Students Based on Academic Characteristics with Deep Learning Approach and Particle Swarm Optimization Algorithm by Dorota Mozyrska, Ewa Pawluszewicz

“…Therefore, the present research tries to present such a system which is based on Natural Language Processing (NLP), feature extraction operations with Particle Swarm Optimization (PSO) algorithm and finally offers suggestions with deep Convolutional Neural Network (CNN). The results show that the accuracy of the proposed approach is higher than previous methods.…”
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Ripples Make Waves: Binding Structured Activity and Plasticity in Hippocampal Networks by Josef H. L. P. Sadowski, Matthew W. Jones, Jack R. Mellor

“…Each step is influenced by distinct neural network states that influence the pattern of activation across cellular assemblies. …”
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