Mechanical Properties Test and Strength Prediction on Basalt Fiber Reinforced Recycled Concrete by Min Huang, Yuru Zhao, Haonan Wang, Shihao Lin

“…In order to study the mechanical properties of basalt fiber reinforced recycled concrete (BFRRC), nine groups of tests are designed with three different replacement rates of recycled aggregates (40%, 70%, and 100%) and volume fraction of basalt fibers (0.1%, 0.2%, and 0.3%). …”
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Real-Time Optical Spectrum Fourier Transform With Time–Bandwidth Product Compression by Hao Sun, Xinyi Zhu, Wei Li, Ninghua Zhu, Ming Li

“…Conventionally, an optical spectrum could be Fourier transformed based on the so-called time-spectrum convolution technique with a linearly dispersive delay line. …”
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INFORMATION TECHNOLOGY FOR RECOGNITION OF ROAD SIGNS USING A NEURAL NETWORK by Elena Yashina, Roman Artiukh, Nikolai Рan, Andrei Zelensky

“…The process of interaction of the system with different data sources is represented by a diagram of precedents. …”
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Neural network analysis of small samples using a large number of statistical criteria to test the sequence of hypotheses about the value of mathematical expectations of correlation... by A.I. Ivanov, A.I. Godunov, E.A. Malygina, N.A. Papusha, A.I. Ermakova

“…The number of hypotheses to be tested must coincide with the number of output states of convolutional artificial neurons. The paper discusses artificial convolutional neurons with output quantizers having 8 quantization thresholds with mathematical expectations E(r) ≈ {0.0; ±0.3; ±0.5; ±0.7; ±0.9} correlation coefficients.…”

Prediction of Mechanical Strength Based on Deep Learning Using the Scanning Electron Image of Microscopic Cemented Paste Backfill by Xuebin Qin, Shifu Cui, Lang Liu, Pai Wang, Mei Wang, Jie Xin

“…In addition, the difference between the measured and predicted values is calculated and the mean and variance of the error are analyzed. …”
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Optimization of Deep Neural Networks Using a Micro Genetic Algorithm by Ricardo Landa, David Tovias-Alanis, Gregorio Toscano

“…This work proposes the use of a micro genetic algorithm to optimize the architecture of fully connected layers in convolutional neural networks, with the aim of reducing model complexity without sacrificing performance. …”
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Exploring the Detection Accuracy of Concrete Cracks Using Various CNN Models by Mohammed Ameen Mohammed, Zheng Han, Yange Li

“…The performance of three different convolutional neural network (CNN) models was then evaluated. …”
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Approximate Crank–Nicolson Algorithm with Higher-Order PML Implementation for Plasma Simulation in Open Region Problems by Liqiang Niu, Yongjun Xie, Jie Gao, Peiyu Wu, Haolin Jiang

“…More precisely, the proposed implementation is based on the CN Direct-Splitting (CNDS) procedure for the finite-difference time-domain (FDTD) unmagnetized plasma simulation. …”
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Vocal performance evaluation of the intelligent note recognition method based on deep learning by Dongyun Chang

“…The accuracy of the model under different feature inputs is compared. The results indicate that different models show obvious differences in F-value, accuracy, precision, and recall. …”
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Large-scale tobacco identification via a very-high-resolution unmanned aerial vehicle benchmark and a ConvFlow Transformer by Wei Han, Shaohao Chen, Shuanglin Xiao, Yunliang Chen, Huihui Zhao, Jining Yan, Xiaohan Zhang, Sheng Wang

“…Then, a dual-branch ConvFlow Transformer is proposed to address tobacco’s rich diversity and high inter-class similarity among different crops. A novel Convolutional Feature-enhanced Multi-Head Self-attention (CF-MHSA) with a location-free design in the ConvFlow Transformer is developed to replace the value matrix in the standard attention with the convolutional multi-scale features, which effectively achieves feature interaction and fusion from the convolutional and transformer branches. …”
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Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images by Veysel Yusuf Cambay, Prabal Datta Barua, Abdul Hafeez Baig, Sengul Dogan, Mehmet Baygin, Turker Tuncer, U. R. Acharya

“…This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to detect various gastrointestinal diseases using a new ResNet50*-based deep feature engineering model with endoscopy images. …”
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Construction of a predictive model for the efficacy of anti-VEGF therapy in macular edema patients based on OCT imaging: a retrospective study by Tingting Song, Boyang Zang, Chui Kong, Xifang Zhang, Huihui Luo, Wenbin Wei, Zheqing Li

“…Therefore, it is crucial to develop automated and efficient methods for predicting therapeutic outcomes.MethodsWe have developed a predictive model for the surgical efficacy in ME patients based on deep learning and optical coherence tomography (OCT) imaging, aimed at predicting the treatment outcomes at different time points. This model innovatively introduces group convolution and multiple convolutional kernels to handle multidimensional features based on traditional attention mechanisms for visual recognition tasks, while utilizing spatial pyramid pooling (SPP) to combine and extract the most useful features. …”
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Research on the Construction of Crossborder e-Commerce Logistics Service System Based on Machine Learning Algorithms by Jinbo Xu, Shibiao Mu

“…The sentiment synthesis word vector is used as the input data structure of the text, the convolutional neural network model and the recurrent neural network model in machine learning are independently designed and constructed, and a shunt is proposed. …”
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Multi-Step Peak Passenger Flow Prediction of Urban Rail Transit Based on Multi-Station Spatio-Temporal Feature Fusion Model by Jianan Sun, Xiaofei Ye, Xingchen Yan, Tao Wang, Jun Chen

“…A combination of a graph convolutional neural network and a Transformer is used. …”
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A Study on Using Transfer Learning to Utilize Information From Similar Systems for Data-Driven Condition Diagnosis and Prognosis by Marcel Braig, Peter Zeiler

“…The former includes condition data of rolling bearings of different dimensioning, recorded under different operating conditions, and the latter includes degradation data of filters with different filtration areas. …”
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Research on leaf identification of table grape varieties based on deep learning by PAN Bowen, LIN Meiling, JU Yanlun, SU Baofeng, SUN Lei, FAN Xiucai, ZHANG Ying, ZHANG Yonghui, LIU Chonghuai, JIANG Jianfu, FANG Yulin

“…The front images of different leaves were taken, and a dataset of 29 713 fresh grape leaves was constructed. …”
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Spatiotemporal Feature Enhancement for Lip-Reading: A Survey by Yinuo Ma, Xiao Sun

“…And each spatiotemporal feature enhancement method was divided into different subclasses based on the differences in the architecture structure, feature attributes, and application types. …”
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EEG–fNIRS signal integration for motor imagery classification using deep learning and evidence theory by Mohammed E. Seno, Niladri Maiti, Maulik Patel, Mihirkumar M. Patel, Kalpesh B. Chaudhary, Ashish Pasaya, Babacar Toure

“…For fNIRS signals, spatial convolution across all channels is employed to explore activation differences among brain regions, and parallel temporal convolution combined with a gated recurrent unit (GRU) captures richer temporal dynamics of the hemodynamic response. …”
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Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data by Bas Peters, Eldad Haber, Keegan Lensink

“…The large spatial/temporal/frequency scale of geoscience and remote-sensing datasets causes memory issues when using convolutional neural networks for (sub-) surface data segmentation. …”
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Novel feature extraction method for signal analysis based on independent component analysis and wavelet transform. by Mariusz Topolski, Jędrzej Kozal

“…However, plenty of proposed methods are based on convolutional neural networks. This class of models requires a high amount of computational power to train and deploy and large dataset. …”
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