Application of BERT-GCN Model Based on Strong Link Relation Graph in Water Use Enterprise Classification by Junhong Xiang, Baoxian Zheng, Chenkai Cai, Shuiping Yao, Shang Gao

“…Due to the poor quality of current water consumption data and the frequent absence of industry information, accurately calculating the water consumption for different industries is difficult. Therefore, we propose a BERT-GCN model based on a strong link graph for classification within the water industry. …”
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Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful? by Ruqayya Awan, Somaya Al-Maadeed, Rafif Al-Saady

“…We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. …”
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Deep Learning for Visual Leading of Ships: AI for Human Factor Accident Prevention by Manuel Vázquez Neira, Genaro Cao Feijóo, Blanca Sánchez Fernández, José A. Orosa

“…To address this issue, this study explores the use of convolutional neural networks (CNNs), evaluating different training strategies and hyperparameter configurations to assist officers in identifying deviations from proper visual leading. …”
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A fine‐grained image classification method based on information interaction by Shuo Zhu, Xukang Zhang, Yu Wang, Zongyang Wang, Jiahao Sun

“…The experimental results show that the method has good generalization on different datasets.…”
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Graph neural networks for mechanical property prediction of 2D fiber composites by Erdem Caliskan, Reza Abedi, Massimiliano Lupo Pasini

“…This work investigates the ability of graph neural networks (GNNs) to homogenize 2D fiber composite microstructures. We use different inhomogeneity and anisotropy indices to motivate and show that the Volume Elements (VEs) used in ML methods should ideally be far from their Representative Volume Element (RVE) size limit and, consequently, are notably anisotropic. …”
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Multifunctional cells based neural architecture search for plant images classification by Lin Huang, Xi Qin, Tiejun Yang

“…Subsequently, an MFC-oriented search strategy is adopted: different shallow blocks from pre-trained models such as MobileNet V3 are searched to construct transfer cell. …”
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Optimizing rainfall-triggered landslide thresholds for daily landslide hazard warning in the Three Gorges Reservoir area by B. Peng, X. Wu

“…Additionally, an innovative application of a three-dimensional convolutional neural network (CNN-3D) model is introduced to enhance the accuracy of landslide susceptibility predictions. …”
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SOH Estimation Method for Lithium-Ion Batteries Using Partial Discharge Curves Based on CGKAN by Shengfeng He, Wenhu Qin, Zhonghua Yun, Chao Wu, Chongbin Sun

“…Finally, multiple experiments under different conditions are conducted, and the results demonstrate that the proposed CGKAN method, by integrating the individual advantages of 1D-CNN, BiGRU, and KAN, efficiently captures complex nonlinear patterns in battery health features and maintains stable performance across various operating conditions.…”
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Unsupervised anomaly detection of permanent-magnet offshore wind generators through electrical and electromagnetic measurements by A. Dibaj, M. Valavi, A. R. Nejad

“…Signals analyzed include three-phase currents, induced shaft voltage, electromagnetic torque, and magnetic flux (air gap and stray) from different directions and positions. The performance of CAE models is compared across time and frequency domains. …”
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Innovative data augmentation strategy for deep learning on biological datasets with limited gene representations focused on chloroplast genomes by Mohammad Ali Abbasi-Vineh, Shirin Rouzbahani, Kaveh Kavousi, Masoumeh Emadpour

“…The current augmentation process is highly adaptable, providing flexibility across different types of biological data repositories. Furthermore, a complementary k-mer-based data augmentation strategy was introduced for unlabeled datasets, enhancing unsupervised analysis. …”
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Optical Fiber Vibration Signal Recognition Based on the EMD Algorithm and CNN-LSTM by Kun Li, Yao Zhen, Peng Li, Xinyue Hu, Lixia Yang

“…Experimental results demonstrate that this method effectively identifies three different types of vibration signals collected from a real-world environment, achieving a recognition accuracy of 97.3% for intrusion signals. …”
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Research on multi-branch residual connection spectrum image classification based on attention mechanism by Zhong Xiaohui, Dong Sheng, Zhang Yiyi, Lu Wei, Jiang Lincen

“…Currently, the extensive use of convolutional neural networks for spectral image classification can extract signal features in the spectrogram, but the redundancy of noisy data generated by a large number of bands of the spectrum affects the feature information at different levels of the image. …”
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Application of Machine Learning in Construction Productivity at Activity Level: A Critical Review by Ying Terk Lim, Wen Yi, Huiwen Wang

“…Noticeably, artificial neural networks, convolutional neural networks, support vector machines, and even deep learning demonstrating have been adopted due to their effectiveness in different functionalities and processes in CPM. …”
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Deep Learning Algorithm for Keratoconus Detection from Tomographic Maps and Corneal Biomechanics: A Diagnostic Study by Wiyada Quanchareonsap, Ngamjit Kasetsuwan, Usanee Reinprayoon, Yonrawee Piyacomn, Thitima Wungcharoen, Monthira Jermjutitham

“…The sample size was divided into the Pentacam and combined Pentacam-Corvis groups. Different convolutional neural network approaches were used to enhance the KC and subclinical KC detection performance. …”
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Research on damage detection technology for wind turbine blade acoustic signals by fusion of sparse representation, compressive sensing and deep learning by Liang Wang, Chun Yang, Chao Yuan, Yanan Liu, Yanqing Chen

“…It has good adaptability under different computing resources, and the processing delay does not exceed 0.45s under complex environments and large data volumes. …”
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A strategy for network multi-layer information fusion based on multimodel in user emotional polarity analysis by Ronghua Wang, Peng Zhuang

“…Then the emotional analysis results of different models were integrated to improve accuracy through a hierarchical information fusion strategy. …”
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6D Pose Estimation Algorithm Based on Improved YOLOv5 With Asymptotic Feature Pyramid Network and Attention Mechanism by Yan Zhang, Hanyu Ye

“…We enhance the original convolutional neural network model by introducing position-aware channel attention into the backbone network, increasing flexibility and precision in feature processing across different positions. …”
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A prototype-based rockburst types and risk prediction algorithm considering intra-class variance and inter-class distance of microseismic data by Xiufeng Zhang, Guoying Li, Yang Chen, Hao Wang, Haikuan Zhang, Haitao Li, Weisheng Du, Xiao Li, Xuewei Xu, Yuze He

“…The results show that the distribution features may be different for the same type of microseismic (MS) and rockburst events, and different types of events may show similar distribution features. …”
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Precision diagnosis of tomato diseases for sustainable agriculture through deep learning approach with hybrid data augmentation by Kamaldeep Joshi, Sahil Hooda, Archana Sharma, Humira Sonah, Rupesh Deshmukh, Narendra Tuteja, Sarvajeet Singh Gill, Ritu Gill

“…The study addresses different challenges faced throughout the model development process, like data scarcity and imbalances. …”
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GLIHamba: global–local context image harmonization based on Mamba by Jinsheng SUN, Jiao PAN, Yu GUO, Chao YAO

“…In contrast, region-based matching methods treat the foreground and background regions as two different styles or domains. Although these methods achieve global consistency in harmonization results, they often overlook the spatial differences between the two regions. …”
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