Construction of a feature gene and machine prediction model for inflammatory bowel disease based on multichip joint analysis by Yan Chaosheng, Sun Haowen, Rao Jingjing, Dai Yuanyuan, Duan Wenhui, Sheng Yingyue, Xue Yuzheng

“…On the basis of methods such as artificial neural networks (ANNs), machine learning techniques, and the SHAP model, we developed a diagnostic model for IBD. …”
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LG-YOLOv8: A Lightweight Safety Helmet Detection Algorithm Combined with Feature Enhancement by Zhipeng Fan, Yayun Wu, Wei Liu, Ming Chen, Zeguo Qiu

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A Lightweight Multi-Scale Context Detail Network for Efficient Target Detection in Resource-Constrained Environments by Kaipeng Wang, Guanglin He, Xinmin Li

“…To meet these challenges, we propose MSCDNet (Multi-Scale Context Detail Network), an innovative and lightweight architecture designed specifically for efficient target detection in such environments. …”
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Gearbox Fault Diagnosis Based on Compressed Sensing and Multi-Scale Residual Network with Lightweight Attention Mechanism by Shihua Zhou, Xinhai Yu, Xuan Li, Yue Wang, Kaibo Ji, Zhaohui Ren

“…Subsequently, a multi-scale feature extraction (MSFE) module was designed based on multi-scale learning, with the aim of improving the feature extraction ability of the signal in noisy environments. …”
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CSSA-YOLO: Cross-Scale Spatiotemporal Attention Network for Fine-Grained Behavior Recognition in Classroom Environments by Liuchen Zhou, Xiangpeng Liu, Xiqiang Guan, Yuhua Cheng

“…To address these issues, we introduce CSSA-YOLO, a novel detection network that incorporates cross-scale feature optimization. …”
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Cross Attention-Based Multi-Scale Convolutional Fusion Network for Hyperspectral and LiDAR Joint Classification by Haimiao Ge, Liguo Wang, Haizhu Pan, Yanzhong Liu, Cheng Li, Dan Lv, Huiyu Ma

“…However, the traditional convolutional neural network fusion techniques always provide poor extraction of discriminative spatial–spectral features from diversified land covers and overlook the correlation and complementarity between different data sources. …”
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Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis by Chaojun Li, Kai Ma, Shengrong Li, Xiangshui Meng, Ran Wang, Daoqiang Zhang, Qi Zhu

“…Dynamic brain networks (DBNs) can capture the intricate connections and temporal evolution among brain regions, becoming increasingly crucial in the diagnosis of neurological disorders. …”
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A fake news detection model using the integration of multimodal attention mechanism and residual convolutional network by Ying Lu, Naiwei Yao

“…Abstract To improve the accuracy and efficiency of fake news detection, this study proposes a deep learning model that integrates residual networks with attention mechanisms. Building on traditional convolutional neural networks, the model incorporates multi-head attention mechanisms to enhance the extraction of key features from multimodal data such as text, images, and videos. …”
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Enhancing maize LAI estimation accuracy using unmanned aerial vehicle remote sensing and deep learning techniques by Zhen Chen, Weiguang Zhai, Qian Cheng

“…Therefore, this study evaluates the potential of multi-source feature fusion and convolutional neural networks (CNN) in estimating maize LAI. …”
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Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition by Osamah Y. Fadhil, Bashar S. Mahdi, Ayad R. Abbas

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A Fuzzy Neural Network-Based Intelligent Prediction Model for Useful Lifespan of Lithium-Ion Batteries by Yaowei Xu, Zhenxing Hao, Wei Li, Angang Cao

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Triple-Stream Deep Feature Selection with Metaheuristic Optimization and Machine Learning for Multi-Stage Hypertensive Retinopathy Diagnosis by Süleyman Burçin Şüyun, Mustafa Yurdakul, Şakir Taşdemir, Serkan Biliş

“…In the first stage, 14 well-known Convolutional Neural Network (CNN) models were evaluated, and the top three models were identified. …”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…The experimental results demonstrate that the BP neural network model incorporating multi-scale features outperforms traditional BP neural network models and other control models in several evaluation metrics. …”
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Context-Aware Level-Wise Feature Fusion Network with Anomaly Focus for Precise Classification of Incomplete Atypical Femoral Fractures in X-Ray Images by Joonho Chang, Junwon Lee, Doyoung Kwon, Jin-Han Lee, Minho Lee, Sungmoon Jeong, Joon-Woo Kim, Heechul Jung, Chang-Wug Oh

“…We also develop a Level-wise Perspective-preserving Fusion Network (LPFN) that preserves the perspective of features while integrating them at different levels to enhance model representation and sensitivity by learning complex correlations and features that are difficult to obtain independently. …”
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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…MobileNet, VGG16, NasNetMobile, DenseNet201, InceptionV3, and Xception were experimented with in the feature extraction and performance evaluation process. …”
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Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection by Omneya Attallah

“…To effectively integrate multiple deep features and diminish the dimensionality of features derived from each CNN, feature transformation and selection methods, including non-negative matrix factorization and Relief-F, are used leading to a reduction in classification complexity. …”
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Financial Evolution and Interdisciplinary Research by Ana Njegovanović

“…This paper (summary of the second chapter of the manuscript "quantum dance") talks about the multidimensionality of finance through evolution, philosophy with interdisciplinary features (interweaving of neuroscience, mathematics, quantum physics, biology and artificial intelligence). …”
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Study on Photovoltaic Plant Site Selection Models Based on Geographic and Environmental Features by RAO Zhi, YANG Zaimin, YANG Xiongping, LI Jiaming, YANG Ping, WEI Zhichu

“…Then， the model leveraged the temporal feature extraction capability of the TCN to perform deep representation learning on preprocessed multisource input data， whereas the former network was employed to capture long-term dependencies. …”
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Development of a Sound Quality Evaluation Model Based on an Optimal Analytic Wavelet Transform and an Artificial Neural Network by Mehdi POURSEIEDREZAEI, Ali LOGHMANI, Mehdi KESHMIRI

“…The feature matrix is fed into the neural network input to determine the psychoacoustic parameters used for sound quality evaluation. …”
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Ghost-Attention-YOLOv8: Enhancing Rice Leaf Disease Detection with Lightweight Feature Extraction and Advanced Attention Mechanisms by Thanh Dang Bui, Tra My Do Le

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