Investigation into the Prediction of Ship Heave Motion in Complex Sea Conditions Utilizing Hybrid Neural Networks by Yuchen Liu, Xide Cheng, Kunyu Han, Zhechun Liu, Baiwei Feng

“…Consequently, this paper proposes a hybrid neural network method that combines Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory Networks (BiLSTMs), and an Attention Mechanism to predict the heaving motion of ships in moderate to complex sea conditions. …”
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Infrared Aircraft Detection Algorithm Based on High-Resolution Feature-Enhanced Semantic Segmentation Network by Gang Liu, Jiangtao Xi, Chao Ma, Huixiang Chen

“…In order to achieve infrared aircraft detection under interference conditions, this paper proposes an infrared aircraft detection algorithm based on high-resolution feature-enhanced semantic segmentation network. Firstly, the designed location attention mechanism is utilized to enhance the current-level feature map by obtaining correlation weights between pixels at different positions. …”
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Infrared Imaging Detection for Hazardous Gas Leakage Using Background Information and Improved YOLO Networks by Minghe Wang, Dian Sheng, Pan Yuan, Weiqi Jin, Li Li

“…Additionally, we incorporate an improved C2f-WTConv module, utilizing wavelet convolution, within the neck stage of the YOLO network. …”
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A Random Degradation Aggregation Network With Temporal-Spatial Attention for Satellite Video Super-Resolution by Lu Li, Mi Wang, Yingdong Pi

“…To address these challenges, we propose an innovative random degradation aggregation network with temporal-spatial attention for satellite VSR. …”
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A novel multi-scale and fine-grained network for large choroidal vessels segmentation in OCT by Wei Huang, Qifeng Yan, Lei Mou, Yitian Zhao, Wei Chen, Wei Chen, Wei Chen

“…The experimental results show that the proposed method has the best performance compared to the most advanced segmentation networks currently available. It is noteworthy that the large choroidal vessels were reconstructed in three dimensions (3D) based on the segmentation results and several 3D morphological parameters were calculated. …”
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Robust DOA Estimation via a Deep Learning Framework with Joint Spatial–Temporal Information Fusion by Yonghong Zhao, Xiumei Fan, Jisong Liu

“…Specifically, we develop a novel CRDCNN-LSTM network architecture, which integrates a Cross-Residual Depthwise Convolutional Neural Network (CRDCNN) with a Long Short-Term Memory (LSTM) module for effective capture of both spatial and temporal features. …”
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EnGCI: enhancing GPCR-compound interaction prediction via large molecular models and KAN network by Weihao Liu, Xiaoli Li, Bo Hang, Pu Wang

“…The MSBM integrates a graph isomorphism network (GIN) and a convolutional neural network (CNN) to extract features from GPCRs and compounds, respectively. …”
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Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN) by C. Selvan, Basha H. Anwar, Soumyalatha Naveen, Shaik Thasleem Bhanu

“…For real-time route optimization, a convolutional neural network (CNN)-based deep learning model is used to adjust ambulance routes based on current traffic and road conditions, achieving an accuracy of 99.15%. …”
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DynseNet: A Dynamic Dense-Connection Neural Network for Land–Sea Classification of Radar Targets by Jingang Wang, Tong Xiao, Kang Chen, Peng Liu

“…The experimental results demonstrate that the proposed attribute recognition method outperforms current deep network architectures.…”
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Reinforced Residual Encoder–Decoder Network for Image Denoising via Deeper Encoding and Balanced Skip Connections by Ismail Boucherit, Hamza Kheddar

“…This paper presents an enhanced residual denoising network, R-REDNet, which stands for Reinforced Residual Encoder–Decoder Network. …”
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LGR-Net: A Lightweight Defect Detection Network Aimed at Elevator Guide Rail Pressure Plates by Ruizhen Gao, Meng Chen, Yue Pan, Jiaxin Zhang, Haipeng Zhang, Ziyue Zhao

“…To solve the problem of excessive model parameters in the original algorithm, we enhance the baseline model’s backbone network by incorporating the lightweight MobileNetV3 and optimize the neck network using the Ghost convolution module (GhostConv). …”
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Research on Fault Detection Technology for Circuit Breaker Operating Mechanism Combinations Based on Deep Residual Networks by Hongping Shao, Yizhe Jiang, Jianeng Zhao, Xueteng Li, Mingzhan Zhang, Mingkun Yang, Xinyu Wang, Hao Yang

“…These spectrograms are then processed using the ResNet50 deep residual neural network for feature extraction and fault classification. …”
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xLSTM Interaction Multilevel SSM-Assisted Decoding Network for Remote Sensing Image Change Detection by Chunpeng Wu, Shuli Cheng, Anyu Du, Liejun Wang, Wenbin Tang

“…With the advancements of convolutional neural networks (CNNs) and Transformers in deep learning, the accuracy of RSCD has significantly improved. …”
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A Rapid Identification Method for Cottonseed Varieties Based on Near-Infrared Spectral and Generative Adversarial Networks by Qingxu Li, Hao Li, Renhao Liu, Xiaofeng Dong, Hongzhou Zhang, Wanhuai Zhou

“…Subsequently, we developed Linear Discriminant Analysis (LDA), Random subspace method (RSM), and convolutional neural network (CNN) models to classify the cottonseed varieties. …”
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Damage Identification of Conduit Rack in Offshore Platform Structures Based on a Novel Composite Neural Network by Jiaqiang Yan, Yuanchao Qiu, Renhe Shao, Ziqiao Ling, Ruixiang Zhang

“…First, the temporal convolutional network (TCN) breaks through the localisation of traditional convolutional neural networks in modelling the temporal dimension by efficiently extracting the long-term time since of the structural vibration response through an expansive causal convolution mechanism. …”
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Azimuth-Guided Feature Embedding Network With Dual Inference Mechanism for Few-Shot SAR Target Recognition by Yan Peng, Xuelian Yu, Haohao Ren, Lei Miao, Lin Zou, Yun Zhou

“…To be specific, the feature extraction model, i.e., AGFEN is composed of the azimuth embedding module (AEM) and the dynamic feature embedding network (DFEN). Among them, AEM resorts to a set of azimuth-parameterized convolution kernels, aiming to make full use of information relevant to the current radar imaging environment. …”
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Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment by C. Labesh Kumar, Suresh Betam, Denis Pustokhin, E. Laxmi Lydia, Kanchan Bala, Rajanikanth Aluvalu, Bhawani Sankar Panigrahi

“…Deep Learning (DL) is one of the influential models useful in cyber-security, and numerous Network Intrusion Detection (NIDS) were developed in current studies. …”
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A Bridge Structure 3D Representation for Deep Neural Network and Its Application in Frequency Estimation by Kejian Hu, Xiaoguang Wu

“…Currently, most predictions related to bridge geometry use shallow neural networks, which limit the network’s ability to fit since the input form limits the depth of the neural network. …”
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MSS-YOLO: Multi-Scale Edge-Enhanced Lightweight Network for Personnel Detection and Location in Coal Mines by Wenjuan Yang, Yanqun Wang, Xuhui Zhang, Le Zhu, Tenghui Wang, Yunkai Chi, Jie Jiang

“…In this paper, we propose a personnel detection network, MSS-YOLO, for fully mechanized mining faces based on YOLOv8. …”
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NEURAL NETWORKS INTEGRATION INTO LEGAL RESOURCES FOR ANTI-СORRUPTION MEASURES IN INTERNATIONAL ECONOMIC CO-OPERATION by Oleksii Makarenkov

“…This issue is further exacerbated by the capabilities of non-anthropogenic neural networks at the current stage of human development. …”
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