Robust Data-Driven Fault Detection: An Application to Aircraft Air Data Sensors by Yunmei Zhao, Hang Zhao, Jianliang Ai, Yiqun Dong

“…Convolutional neural networks (CNN) and long-short time memory (LSTM) blocks are used in the DNN scheme for accurate FD performances. …”
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Quantum theory-inspired inter-sentence semantic interaction model for textual adversarial defense by Jiacheng Huang, Long Chen, Xiaoyin Yi, Ning Yu

“…Abstract Deep neural networks have a recognized susceptibility to diverse forms of adversarial attacks in the field of natural language processing and such a security issue poses substantial security risks and erodes trust in artificial intelligence applications among people who use them. …”
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Assessment of Machine Learning Algorithms in Short-term Forecasting of PM10 and PM2.5 Concentrations in Selected Polish Agglomerations by Bartosz Czernecki, Michał Marosz, Joanna Jędruszkiewicz

“…We tested four ML models: AIC-based stepwise regression, two tree-based algorithms (random forests and XGBoost), and neural networks. Employing analysis and cross-validation, we found that XGBoost performed the best, followed by random forests and neural networks, and stepwise regression performed the worst. …”
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Comparative Analysis of Vanilla CNN and Transfer Learning Models for Glaucoma Detection by Brendan Ubochi, Abayomi E. Olawumi, John Macaulay, Oyawoye I. Ayomide, Kayode F. Akingbade

“…Models that are based on the convolutional neural networks (CNNs) have shown promise in the early detection of glaucoma. …”
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A Review of Reinforcement Learning for Fixed-Wing Aircraft Control Tasks by David J. Richter, Ricardo A. Calix, Kyungbaek Kim

“…A lot of that can be attributed to the recent advancements in machine learning (ML) and deep learning (DL) as a whole, the power of deep neural networks and the incorporation of them into reinforcement learning algorithms and techniques. …”
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A Computational Approach to Understanding Agglutinative Structures in Urdu by Muhammad Shoaib Tahir, Mahnoor Amjad

“…These modern approaches, particularly Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs), show promise in accurately modeling Urdu's agglutinative morphology, though they require extensive linguistic data and computational resources. …”
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On the choice of the method of dynamic rationing of energy resources in oil refineries by V. R. Vedruchenko, E. M. Rezanov, A. P. Starikov, A. V. Kushnarenko, P. A. Surovtsev, V. A. Kikhtenko

“…In order to obtain predictive data, linear regression, machine learning, and neural networks are proposed to be used to build a mathematical model. …”
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Almost Periodic Functions on Time Scales and Applications by Yongkun Li, Chao Wang

“…Based on these results, a class of high-order Hopfield neural networks with variable delays are studied on almost periodic time scales, and some sufficient conditions are established for the existence and global asymptotic stability of the almost periodic solution. …”
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Time Complexity of Training DNNs With Parallel Computing for Wireless Communications by Pengyu Cong, Chenyang Yang, Shengqian Han, Shuangfeng Han, Xiaoyun Wang

“…Deep neural networks (DNNs) have been widely used for learning various wireless communication policies. …”
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UAV Hyperspectral Remote Sensing Image Classification: A Systematic Review by Zhen Zhang, Lehao Huang, Qingwang Wang, Linhuan Jiang, Yemao Qi, Shunyuan Wang, Tao Shen, Bo-Hui Tang, Yanfeng Gu

“…This article provides an in-depth and systematic review of UAV HSI classification techniques, systematically examining the evolution from traditional machine learning approaches, such as sparse coding, compressed sensing, and kernel methods, to cutting-edge deep learning frameworks, including convolutional neural networks, Transformer models, recurrent neural networks, graph convolutional networks, generative adversarial networks, and hybrid models. …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…Several machine learning models, including convolutional neural networks, recurrent neural networks, and long short-term memory, have been employed to enhance EVCS security. …”
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CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer by Kai Liu, Tao Ren, Zhangli Lan, Yang Yang, Rong Liu, Yuantong Xu

“…To address this issue, this study proposes CGV-Net (CNN, GNN, and ViT networks), a novel tunnel crack segmentation network model that integrates convolutional neural networks (CNNs), graph neural networks (GNNs), and Vision Transformers (ViTs). …”
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Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics by F. Cadini, E. Zio, N. Pedroni

“…Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. …”
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Interneuronal modulations as a functional switch for cortical computations: mechanisms and implication for disease by Yann Zerlaut, Alexandra Tzilivaki, Alexandra Tzilivaki, Alexandra Tzilivaki

“…In this perspective, we propose that specific types of interneurons may play a complementary role, by modulating the computational properties of neural networks. We review experimental and theoretical evidence, mainly from rodent sensory cortices, that supports this view. …”
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COMPARING BRAIN ACTIVITY OF ENTREPRENEURS AND NON-ENTREPRENEURS DURING CREATIVE THINKING AND OPPORTUNITY RECOGNITION by Burcu Demirkundak, Ayşe İrmiş, Hicran Utkun Dincer Aydın

“…In addition, it has been observed different neural networks in the brains of entrepreneurs, especially during opportunity recognition.…”
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Research on Face Recognition Method by Autoassociative Memory Based on RNNs by Qi Han, Zhengyang Wu, Shiqin Deng, Ziqiang Qiao, Junjian Huang, Junjie Zhou, Jin Liu

“…The model is based on the recurrent neural networks (RNNs) for face recognition, under the condition that the face database is replaced by its model parameters. …”
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PYTHON INTERFACE DESIGN FOR MICROPHOTOGRAPHY ANALYSIS:APPLICATION TO EVALUATE THE HEMORHEOLOGICAL ACTIVITY OF QUERCETIN by P.Buszniez, M. Gómez, H. V. Castellini, B.D. Riquelme

“…The image processing algorithms are contained in the OpenCV2 library, which uses pre-trained neural networks. Images were obtained usinga digital camera coupled to an inverted microscope (40x objective). …”
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Surface Approximation using Growing Self-Organizing Nets and Gradient Information by Jorge Rivera-Rovelo, Eduardo Bayro-Corrochano

“…In this paper we show how to improve the performance of two self-organizing neural networks used to approximate the shape of a 2D or 3D object by incorporating gradient information in the adaptation stage. …”
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Efficient Prediction of Network Traffic for Real-Time Applications by Muhammad Faisal Iqbal, Muhammad Zahid, Durdana Habib, Lizy Kurian John

“…Many predictors from three different classes, including classic time series, artificial neural networks, and wavelet transform-based predictors, are compared. …”
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Use of Arduino for Monitoring the Air Quality of Indoor Environments by Felipe Macedo Freitas Siqueira, Lizandro de Sousa Santos

“…Another approach, based on artificial neural networks, was formulated in which the parameters were used as input arguments of the network and the TCI was used as a target parameter. …”
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