Physics-Informed Neural Network-Based Input Shaping for Vibration Suppression of Flexible Single-Link Robots by Tingfeng Li, Tengfei Xiao

Subjects: “…physics-informed neural network (PINN)…”
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A novel hybrid inception-xception convolutional neural network for efficient plant disease classification and detection by Wasswa Shafik, Ali Tufail, Chandratilak Liyanage De Silva, Rosyzie Anna Awg Haji Mohd Apong

“…This study presents a novel hybrid inception-xception (IX) using a convolution neural network (CNN). The presented model combines inception and depth-separable convolution layers to capture multiple-scale features while reducing model complexity and overfitting. …”
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Event-Triggered State Estimation for a Class of Delayed Recurrent Neural Networks with Sampled-Data Information by Hongjie Li

“…The paper investigates the state estimation problem for a class of recurrent neural networks with sampled-data information and time-varying delays. …”
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Adaptive Event-Triggered Synchronization of Networked Neural Networks with Time-Varying Delay Subject to Actuator Saturation by Yao Xu, Renren Wang, Hongqian Lu, Xingxing Song, Yahan Deng, Wuneng Zhou

“…This paper discusses the adaptive event-triggered synchronization problem of a class of neural networks (NNs) with time-varying delay and actuator saturation. …”
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Adaptive Neural Network Variable Structure Control for Liquid-Filled Spacecraft under Unknown Input Saturation by Hongwei Wang, Shufeng Lu, Xiaojuan Song

“…Also, the saturation compensation scheme is derived by using a radial basis function neural network to approximate the unknown saturation nonlinearity. …”
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3D Face Modeling Algorithm for Film and Television Animation Based on Lightweight Convolutional Neural Network by Cheng Di, Jing Peng, Yihua Di, Siwei Wu

“…Through the analysis of facial feature extraction technology, this paper designs a lightweight convolutional neural network (LW-CNN). The LW-CNN model adopts a separable convolution structure, which can propose more accurate features with fewer parameters and can extract 3D feature points of a human face. …”
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A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions by Xi Xi, Jiaqi Li, Jinmeng Jia, Qiuchen Meng, Chen Li, Xiaowo Wang, Lei Wei, Xuegong Zhang

“…This method to analyze single-cell multi-omics data demonstrates how the interpretable design of neural networks can better decode biological systems.…”
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A Hybrid Approach for Modular Neural Network Design Using Intercriteria Analysis and Intuitionistic Fuzzy Logic by Sotir Sotirov, Evdokia Sotirova, Vassia Atanassova, Krassimir Atanassov, Oscar Castillo, Patricia Melin, Todor Petkov, Stanimir Surchev

“…Here, the proposed method is applied to study the behavior of one type of neural networks, the modular neural networks (MNN), that combine several simple neural models for simplifying a solution to a complex problem. …”
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An Efficient 3D Convolutional Neural Network for Dose Prediction in Cancer Radiotherapy from CT Images by Lam Thanh Hien, Pham Trung Hieu, Do Nang Toan

“…<b>Materials and Methods</b>: In this paper, we propose a custom 3D convolutional neural network model with a U-Net-based architecture to automatically predict radiation doses during cancer radiation therapy from CT images. …”
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C1-Almost Periodic Solutions of BAM Neural Networks with Time-Varying Delays on Time Scales by Yongkun Li, Lili Zhao, Li Yang

“…On a new type of almost periodic time scales, a class of BAM neural networks is considered. By employing a fixed point theorem and differential inequality techniques, some sufficient conditions ensuring the existence and global exponential stability of C1-almost periodic solutions for this class of networks with time-varying delays are established. …”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

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A stochastic artificial neural network model for investigating street vendor behavior in a night market by Pao-Kuan Wu, Tsung-Chih Hsiao, Ming Xiao

“…This article offers a hybrid computational approach that combines an artificial neural network with Bayesian probability to improve on the conventional artificial neural network model. …”
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An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions by Sehmus Fidan, Hasan Oktay, Suleyman Polat, Sarper Ozturk

“…Then, the Levenberg–Marquardt algorithm was used for training the neural network in the single hidden layer using 5, 10, 15, 20, and 25 neurons, respectively. …”
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Cyclic Training of Dual Deep Neural Networks for Discovering User and Item Latent Traits in Recommendation Systems by Dohyoung Rim, Sirojiddin Nuriev, Younggi Hong

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Hybrid Adaptive Pinning Control for Function Projective Synchronization of Delayed Neural Networks with Mixed Uncertain Couplings by T. Botmart, N. Yotha, P. Niamsup, W. Weera

“…This paper presents the function projective synchronization problem of neural networks with mixed time-varying delays and uncertainties asymmetric coupling. …”
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Prediction of Mechanical Strength of Fiber Admixed Concrete Using Multiple Regression Analysis and Artificial Neural Network by S. Karthiyaini, K. Senthamaraikannan, J. Priyadarshini, Kamal Gupta, M. Shanmugasundaram

“…The present study is to compare the multiple regression analysis (MRA) model and artificial neural network (ANN) model designed to predict the mechanical strength of fiber-reinforced concrete on 28 days. …”
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Sistem Rekognisi Citra Digital Bahasa Isyarat Menggunakan Convolutional Neural Network dan Spatial Transformer by Mohammad Alfiano Rizky Mahardika, Novanto Yudistira, Achmad Ridok

Subjects: “…Convolutional Neural Network…”
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Research on Ethanol Coupling to Prepare C4 Olefins Based on BP Neural Network and Cluster Analysis by Sheng-Mei Zhang, Wen-Li Zhan, Han Hu, Yu-Shu Liu, Jia-Ming Zhu

“…Finally, according to the three-dimensional spatial visualization analysis and using the BP neural network model training data, we obtain that under the conditions of using loading method I, catalyst combination type 200 mg 0.5 wt% Co/SiO2-200 mg HAP-ethanol concentration 0.9 ml/min and temperature 450°C, the yield of C4 olefins can reach the maximum. …”
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Predicting drug combination side effects based on a metapath-based heterogeneous graph neural network by Leixia Tian, Qi Wang, Zhiheng Zhou, Xiya Liu, Ming Zhang, Guiying Yan

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Automatic Detection of Small Intestinal Hookworms in Capsule Endoscopy Images Based on a Convolutional Neural Network by Tao Gan, Yulin Yang, Shuaicheng Liu, Bing Zeng, Jinlin Yang, Kai Deng, Junchao Wu, Li Yang

“…We sought to develop an artificial intelligence system with a convolutional neural network (CNN) to automatically detect hookworms in CE images. …”
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