Multi-Scale Feature Extraction with 3D Complex-Valued Network for PolSAR Image Classification by Nana Jiang, Wenbo Zhao, Jiao Guo, Qiang Zhao, Jubo Zhu

“…This strategy enhances information utilization by integrating multi-scale receptive fields, complementing feature advantages. …”
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Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

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Multi‑feature geological hazard susceptibility assessment by integrating improved ResNet and transfer learning: A case study of the Loess Plateau in Northern Shaanxi by Hao Cheng, Chong Xu, Rong Guo, Hai-kun Jing, Zeng-lin Hong, Feng-chen Fu, Ruo-shu Li

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Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder by Elahe Hosseini, Seyyed Ali Hosseini, Stijn Servaes, Brandon Hall, Pedro Rosa-Neto, Ali-Reza Moradi, Ajay Kumar, Mir Mohsen Pedram, Sanjeev Chawla

“…<b>Conclusions:</b> Our findings demonstrate that the proposed approach of extracting 2D features from 3D MRI images and integrating these features with clinical characteristics may be useful in the diagnosis of ADHD with high accuracy.…”
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Aspect Sentiment Triplet Extraction with Syntax-Semantics Graph Convolutional Network by Jingyun Zhang, Shuwei Xu, Xin Gao, Zhiwei Tang

“…Abstract In the traditional task of aspect sentiment triplet extraction, existing approaches typically focus on either syntactic or semantic features independently, failing to leverage the complementary integration of these two types of information. …”
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A novel multiscale feature enhancement network using learnable density map for red clustered pepper yield estimation by Chenming Cheng, Chenming Cheng, Jin Lei, Jin Lei, Zicui Zhu, Lijian Lu, Lijian Lu, Zhi Wang, Zhi Wang, Jiali Tao, Jiali Tao, Xinyan Qin, Xinyan Qin

“…Then, a novel MFEN was developed to improve feature extraction from these density maps. This network combines dilation convolution, residual structures, and an attention mechanism to effectively extract features. …”
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Lane line detection based on cross-convolutional hybrid attention mechanism by Jianping Wen, Zhuang Zhao, Chenze Wang, Ze Sun, Chao Xu

“…Unlike traditional approaches that separately employ channel and spatial attention, our proposed mechanism integrates these modalities through cross-convolution, thereby enabling cross-group feature interaction and dynamic spatial weight allocation. …”
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Integrating fast iterative filtering and ensemble neural network structure with attention mechanism for carbon price forecasting by Wang Zhong, Wang Yue, Wang Haoran, Tang Nan, Wang Shuyue

“…First, the carbon price series is decomposed into a series of smoother subsequences using fast iterative filtering (FIF). Subsequently, an integrated prediction model, AM-TCN-LSTM, is constructed, incorporating the attention mechanism (AM), temporal convolutional networks (TCN), and long short-term memory (LSTM) neural networks. …”
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Dynamic Hypergraph Convolutional Networks for Hand Motion Gesture Sequence Recognition by Dong-Xing Jing, Kui Huang, Shi-Jian Liu, Zheng Zou, Chih-Yu Hsu

“…This paper introduces a novel approach to hand motion gesture recognition by integrating the Fourier transform with hypergraph convolutional networks (HGCNs). …”
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DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification by Musa Adamu Wakili, Harisu Abdullahi Shehu, Mahdi Abdollahi, Badamasi Imam Ya'u, Md Haidar Sharif, Huseyin Kusetogullari

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Invertible Attention-Guided Adaptive Convolution and Dual-Domain Transformer for Pansharpening by Qun Song, Hangyuan Lu, Chang Xu, Rixian Liu, Weiguo Wan, Wei Tu

“…However, existing techniques face challenges in integrating long-range dependencies to correct locally misaligned features, which results in spatial-spectral distortions. …”
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A point cloud segmentation network with hybrid convolution and differential channels by Xiaoyan Zhang, Yantao Bu

“…Specifically, we design a hybrid convolutional feature extraction (HCFE) module for processing 3D semantic information and spatial information independently, using different convolution kernels to obtain the subtle geometric structure differences between points. …”
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A Hybrid Deep Learning Approach for Bearing Fault Diagnosis Using Continuous Wavelet Transform and Attention-Enhanced Spatiotemporal Feature Extraction by Muhammad Farooq Siddique, Faisal Saleem, Muhammad Umar, Cheol Hong Kim, Jong-Myon Kim

“…This study presents a hybrid deep learning approach for bearing fault diagnosis that integrates continuous wavelet transform (CWT) with an attention-enhanced spatiotemporal feature extraction framework. …”
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MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models by Feng Wang, Jinming Chu, Liyan Shen, Shan Chang

“…Then, Fusion Autoencoder (FAE) is used to integrate these multimodal features, generating rich and balanced protein representations. …”
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Multichannel convolutional transformer for detecting mental disorders using electroancephalogrpahy records by Mamadou Dia, Ghazaleh Khodabandelou, Syed Muhammad Anwar, Alice Othmani

“…Our proposed model, the multichannel convolutional transformer, integrates the strengths of both convolutional neural networks and transformers. …”
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AI Knows Aesthetics: AI-Generated Interior Design Identification Using Deep Learning Algorithms by Fei Liu, Kailing Deng

“…The integration of Artificial Intelligence (AI) in interior design has revolutionized how spaces are conceptualized, visualized, and classified. …”
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Remaining useful life prediction of li-ion batteries based on an improved transformer model by Qingsong Wang, Annuo Yu, Hao Ding, Ming Cheng, Giuseppe Buja

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CNN-SENet: a GNSS-R ocean wind speed retrieval model integrating CNN and SENet attention mechanism by Yimin Xia, Dongliang Guan, Zhiling Zhou

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SMS spam detection using BERT and multi-graph convolutional networks by Linjie Shen, Yanbin Wang, Zhao Li, Wenrui Ma

“…This multigraph approach captures diverse features and models both global and local structures using tailored Graph Convolutional Networks. …”
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An improved EAE-DETR model for defect detection of server motherboard by Jian Chi, Mingke Zhang, Puhon Zhang, Guowang Niu, Zhihao Zheng

“…Lastly, we constructed the EUCB-SC upsampling module, which integrates depth convolution and channel shuffling strategies to enhance feature reconstruction efficiency. …”
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