Displacement-Based Back-Analysis of the Model Parameters of the Nuozhadu High Earth-Rockfill Dam by Yongkang Wu, Huina Yuan, Bingyin Zhang, Zongliang Zhang, Yuzhen Yu

“…In this method, an artificial neural network is used as a substitute for time-consuming finite element analysis, and an evolutionary algorithm is applied for both network training and parameter optimization. …”
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An improved quantitative assessment method on hazardous interference of power lines to the signal cable in high‐speed railway by Chang Liu, Shiwu Yang, Yong Cui, Shaotong Chu, Qihui Xiong

“…Abstract High‐speed railway (HSR) presents the characteristics of a heavy load, large traction current, and ballastless track‐bed. As the 'neural network' of the signalling system, the line‐side signal cable may threaten both human safety and control information transmission for an HSR operation when interfered with by a strong traction current. …”
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Automatic MRI Image Classification Using Attention and Residual CNNs With Enhanced Image Denoising Filters by Suganya Athisayamani, A. Robert Singh, Faten Khalid Karim, Samih M. Mostafa

“…The enhanced image features are used for classification with three different CNN classification models: Convolutional Neural Network (CNN), CNN with attention module (CNN-AM) and CNN with a residual module (CNN-RM). …”
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Dynamic Learning from Adaptive Neural Control of Uncertain Robots with Guaranteed Full-State Tracking Precision by Min Wang, Yanwen Zhang, Huiping Ye

“…By combining two independent Lyapunov functions and radial basis function (RBF) neural network (NN) approximator, a novel and simple adaptive neural control scheme is proposed for the dynamics of the unconstrained transformation errors, which guarantees uniformly ultimate boundedness of all the signals in the closed-loop system. …”
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Deep Learning Approach for Automatic Classification of Ocular and Cardiac Artifacts in MEG Data by Ahmad Hasasneh, Nikolas Kampel, Praveen Sripad, N. Jon Shah, Jürgen Dammers

“…We propose an artifact classification scheme based on a combined deep and convolutional neural network (DCNN) model, to automatically identify cardiac and ocular artifacts from neuromagnetic data, without the need for additional electrocardiogram (ECG) and electrooculogram (EOG) recordings. …”
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2.5D Facial Personality Prediction Based on Deep Learning by Jia Xu, Weijian Tian, Guoyun Lv, Shiya Liu, Yangyu Fan

“…Our experimental results show that the deep neural network trained by large labeled datasets can reliably predict people’s multidimensional personality characteristics through 2.5D static facial contour images, and the prediction accuracy is better than the previous method using 2D images.…”
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SVDD: SAR Vehicle Dataset Construction and Detection by Dan Gao, Xiaofang Wu, Zhijin Wen, Yue Xu, Zhengchao Chen

“…With the advent of high-quality SAR images and the rapid development of computing technology, the object detection algorithms based on convolution neural network have attracted a lot of attention in the field of SAR object detection. …”
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Reconstruction of Three-Dimensional Porous Media Using Deep Transfer Learning by Yi Du, Jie Chen, Ting Zhang

“…Hence, a method for reconstructing porous media is presented by applying DTL to extract features from a training image (TI) of porous media to replace the process of scanning a TI for different patterns as in multiple-point statistical methods. The deep neural network is practically used to extract the complex features from the TI of porous media, and then, a reconstructed result can be obtained by transfer learning through copying these features. …”
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Validation of the New Algorithm for Rain Rate Retrieval from AMSR2 Data Using TMI Rain Rate Product by Elizaveta Zabolotskikh, Bertrand Chapron

“…AMSR2 brightness temperature differences at C- and X-band channels are then used as inputs to train a neural network (NN) function for RR retrieval. Validation is performed against Tropical Rain Measurement Mission (TRMM) Microwave Instrument (TMI) RR products. …”
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Neural-field-based image reconstruction for bioluminescence tomography by Xuanxuan Zhang, Xu Cao, Jiulou Zhang, Lin Zhang, Guanglei Zhang

“…The proposed NF-based method establishes a transformation between the coordinate of an arbitrary spatial point and the source value of the point with a relatively light-weight multilayer perceptron, which has remarkable computational efficiency. Another simple neural network composed of two fully connected layers and a 1D convolutional layer is used to generate the neural features. …”
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Reconfigurable and nonvolatile ferroelectric bulk photovoltaics based on 3R-WS2 for machine vision by Yue Gong, Ruihuan Duan, Yi Hu, Yao Wu, Song Zhu, Xingli Wang, Qijie Wang, Shu Ping Lau, Zheng Liu, Beng Kang Tay

“…Further, we integrate this system with a convolutional neural network to achieve high-accuracy (100%) color image recognition at σ = 0.3 noise level within six epochs. …”
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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

“…The FWOA-SVR model is comprehensively evaluated against traditional SVR, Long Short-Term Memory (LSTM), and Backpropagation Neural Network (BPNN) models using training, validation, and testing datasets. …”
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Stripe segmentation of oceanic internal waves in SAR images based on SegFormer by Hong-Sheng Zhang, Ji-Yu Sun, Kai-Tuo Qi, Ying-Gang Zheng, Jiao-Jiao Lu, Yu Zhang

“…Comparative experimental results demonstrated that SegFormer outperformed other models, including U-Net, Fast-SCNN (Fast Segmentation Convolutional Neural Network), ORCNet (Ocular Region Context Network), and PSPNet (Pyramid Scene Parsing Network), efficiently and accurately segmenting marine internal wave stripes in SAR images. …”
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Multimodal Multiobject Tracking by Fusing Deep Appearance Features and Motion Information by Liwei Zhang, Jiahong Lai, Zenghui Zhang, Zhen Deng, Bingwei He, Yucheng He

“…After that, we use Convolutional Neural Network (CNN) to learn the deep appearance features of objects and employ Kalman Filter to obtain the motion information of objects. …”
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METAGRAPH THEORY AS A BASIS FOR MODELING RELEVANT MEDIA DISCOURSE by Yuriy E. Gapanyuk

“…Despite significant advances in the field of neural network text processing, the task of modeling text and media discourse remains relevant. …”
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Prediction of power generation and maintenance using AOC‐ResNet50 network by Yueqiang Chu, Wanpeng Cao, Cheng Xiao, Yubin Song

“…Based on the analysis of the OctConv (Octave Convolution) network structure, the AOctConv (Attention Octave Convolution) convolutional neural network structure is proposed, which is combined with the ResNet50 backbone network to obtain AOC‐ResNet50. …”
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Predicting and evaluating the engineering properties of civic garbage torched bottom ash and sisal fibre-reinforced earth blocks by Abinaya Thennarasan Latha, Balasubramanian Murugesan

“…The properties are predicted using artificial neural network (ANN) analysis and response surface methodology (RSM). …”
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Accelerating materials property prediction via a hybrid Transformer Graph framework that leverages four body interactions by Mohammad Madani, Valentina Lacivita, Yongwoo Shin, Anna Tarakanova

“…We propose a framework utilizing a Graph Neural Network with composition-based and crystal structure-based architectures, combined with a transfer learning scheme. …”
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Recycled integrated circuit detection using reliability analysis and machine learning algorithms by Udaya Shankar Santhana Krishnan, Kalpana Palanisamy

“…In this work, three machine learning methods, namely K‐means clustering, back propagation neural network (BPNN) and support vector machines (SVMs), are used to detect the recycled IC aged for a shorter period (1 day) with minimum data size. …”
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A Novel Technique for Handwritten Signature Recognition by Leila Boucerredj, Karima Kechroud, Bouaziz Noureddine, Abderrahmane Khechekhouche

“…This paper introduces a novel deep learning approach utilizing a convolutional neural network (CNN) architecture specifically designed for HSR. …”
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