Uncertainty prediction of wind speed based on improved multi-strategy hybrid models by Xinyi Xu, Shaojuan Ma, Cheng Huang

“…Finally, the NOA-BiTCN-BiGRU model was built to perform wind speed interval prediction. …”
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Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems by Saud S. Alotaibi, Turki Ali Alghamdi

“…The comparison study of the CLAFS-ODLCD method portrayed a superior accuracy value of 99.48% over existing models.…”
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Lung adenocarcinoma subtype classification based on contrastive learning model with multimodal integration by Changmiao Wang, Lijian Liu, Chenchen Fan, Yongquan Zhang, Zhijun Mai, Li Li, Zhou Liu, Yuan Tian, Jiahang Hu, Ahmed Elazab

“…Finally, we employ focal loss to mitigate the effects of unbalanced classes and contrastive learning loss to enhance feature representation and improve the model’s performance. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…This reduces unnecessary computational overhead while preserving the integrity of critical feature information, thus significantly cutting down on the model’s parameters and computational demands. …”
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An Efficient Sentiment Classification Method with the Help of Neighbors and a Hybrid of RNN Models by Israa K. Salman Al-Tameemi, Mohammad-Reza Feizi-Derakhshi, Saeed Pashazadeh, Mohammad Asadpour

“…Motivated by this intuition, a novel deep text sentiment classification (DTSC) model is proposed to improve the model’s performance by incorporating the neighborhood of related texts. …”
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DMFFT: improving the generation quality of diffusion models using fast Fourier transform by Cuihong Yu, Cheng Han, Chao Zhang

“…Abstract In this study, we demonstrate the significant development potential of diffusion U-Net extraction features transferred to the frequency domain, opening up a new perspective for diffusion models and generating a new optimization idea for diffusion model-related research. …”
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Research on Network Intrusion Detection Model Based on Hybrid Sampling and Deep Learning by Derui Guo, Yufei Xie

“…This study proposes an enhanced network intrusion detection model, 1D-TCN-ResNet-BiGRU-Multi-Head Attention (TRBMA), aimed at addressing the issues of incomplete learning of temporal features and low accuracy in the classification of malicious traffic found in existing models. …”
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Homeostatic synaptic normalization optimizes learning in network models of neural population codes by Jonathan Mayzel, Elad Schneidman

“…Incorporating more biological features and utilizing synaptic normalization in the learning process, results in accurate models that are more efficient. …”
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Representation Learning for Vision-Based Autonomous Driving via Probabilistic World Modeling by Haoqiang Chen, Yadong Liu, Dewen Hu

“…Representation learning plays a vital role in autonomous driving by extracting meaningful features from raw sensory inputs. World models emerge as an effective approach to representation learning by capturing predictive features that can anticipate multiple possible futures, which is particularly suited for driving scenarios. …”
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Clinical characteristics, prognosis, and predictive modeling in class IV ± V lupus nephritis by Anjing Wang, Anjing Wang, Yunlong Qin, Yunlong Qin, Yan Xing, Zixian Yu, Liuyifei Huang, Jinguo Yuan, Yueqing Hui, Mei Han, Guoshuang Xu, Jin Zhao, Shiren Sun

“…ObjectiveThe objective of this study is to compare the clinical features and survival outcomes of class IV ± V lupus nephritis (LN) patients, identify risk factors, and develop an accurate prognostic model.MethodsThis study enrolled patients diagnosed with class IV ± V LN by renal biopsy at Xijing Hospital from December 2013 to June 2023. …”
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Intention Recognition of AAV Swarm Based on GAT-EPool-BiGRU Model by Jiajun Yuan, Xiang Jia, Yu An, Liang Geng, Lei Shu

“…This performance improvement stems from GAT’s dynamic graph construction capability, EPool’s key feature retention mechanism, and BiGRU’s bidirectional temporal processing, collectively enhancing both robustness and accuracy in intent recognition. …”
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Inversion of County-Level Farmland Soil Moisture Based on SHAP and Stacking Models by Hui Zhan, Peng Guo, Jiaxin Hao, Jiali Li, Zixu Wang

“…We then applied Shapley Additive exPlanations (SHAP) for feature selection, and a Stacking model was used to perform soil moisture inversion based on the selected features. …”
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Identification of water sources of mine water bursts based on the FPS-DT model by Kaide Liu, Yu xia, Xiaolong Li, Chaowei Sun, Wenping Yue, Qiyu Wang, Songxin Zhao, Shufeng Chen

“…To validate the model’s performance, five-fold cross-validation was used for evaluation. …”
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Convolutional spatio-temporal sequential inference model for human interaction behavior recognition by Lizhong Jin, Rulong Fan, Xiaoling Han, Xueying Cui

“…The model extracts features from skeleton sequences using DINet and from RGB video frames using ResNet-18. …”
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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

“…Performance comparison with existing approaches also shows the superior performance of the proposed model.…”
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DSNET: A Lightweight Segmentation Model for Segmentation of Skin Cancer Lesion Regions by Yucong Chen, Guang Yang, Xiaohua Dong, Junying Zeng, Chuanbo Qin

“…Currently, most skin disease segmentation tasks tend to use large models to achieve better segmentation performance. …”
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Enhanced Credit Card Fraud Detection Using Deep Hybrid CLST Model by Madiha Jabeen, Shabana Ramzan, Ali Raza, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

“…Furthermore, SMOTE is used to balance the data and hyperparameter tuning is utilized to achieve the best model performance. In the case of hyperparameter tuning, the detection rate is greatly enhanced. …”
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Bubble Temperature Effect on the Heat Transfer Performance of R449a During Flow Boiling Inside a Horizontal Smooth Tube by Andrea Lucchini, Bharath Nagaraju, Igor Matteo Carraretto, Luigi Pietro Maria Colombo, Domenico Mazzeo, Luca Molinaroli, Paola Grazia Pittoni

“…Nevertheless, for both quantities, other correlations with similar performances are available.…”
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Magnetic resonance radiomics-based deep learning model for diagnosis of Alzheimer's disease by Zengbei Yuan, Na Qi, Xing Chen, Yingying Luo, Zirong Zhou, Jie Wang, Junhao Wu, Jun Zhao

“…Finally, the selected radiomic features were used to implement the AD diagnosis task with the TabNet model. …”
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Different radiomics models in predicting the malignant potential of small intestinal stromal tumors by Yuxin Xie, Chongfeng Duan, Xuzhe Zhou, Xiaoming Zhou, Qiulin Shao, Xin Wang, Shuai Zhang, Fang Liu, Zhenbo Sun, Ruirui Zhao, Gang Wang

“…Nomogram model was developed by combining clinical data and radiomics features. …”
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