Image Experience Prediction for Historic Districts Using a CNN-Transformer Fusion Model by Weijia Wang, Youping Teng, Lu Yan, Longwei Wu, Yinying Yang, Zijian Luo

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Cattle welfare assessment based on adaptive fuzzy logic and multimodal data fusion by Lei Tong, Lei Tong, Lei Tong, Jiandong Fang, Jiandong Fang, Jiandong Fang, Xiuling Wang, Xiuling Wang, Xiuling Wang, Yudong Zhao, Yudong Zhao

“…The method establishes a quantitative scoring system based on behavioral duration and individual group differences, and designs a multi-modal data processing framework that combines Backpropagation (BP) neural networks with adaptive fuzzy logic. This framework uses a Gaussian membership function to replace the traditional triangular membership function for feature mapping, significantly improving the robustness and accuracy of the evaluation system through a differentiated weight allocation strategy. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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Assessment of Knot-Induced Degradation in Timber Beams: Probabilistic Modeling and Data-Driven Prediction of Load Capacity Loss by Peixuan Wang, Guoming Liu, Fanrong Li, Shengcai Li, Gabriele Milani, Donato Abruzzese

“…Finally, a predictive model based on a fully connected neural network is developed; feature analysis indicates that the longitudinal position of knots exerts a stronger nonlinear influence on load capacity than radial depth or diameter. …”
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Practical guidelines for cell segmentation models under optical aberrations in microscopy by Boyuan Peng, Jiaju Chen, P. Bilha Githinji, Ijaz Gul, Qihui Ye, Minjiang Chen, Peiwu Qin, Xingru Huang, Chenggang Yan, Dongmei Yu, Jiansong Ji, Zhenglin Chen

“…Deep learning methods, particularly convolutional neural networks (CNNs), have revolutionized cell segmentation by extracting intricate features from images. …”
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Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures by Budi Sunarko, Agung Adi Firdaus, Yudha Andriano Rismawan, Anan Nugroho

“…This study aimed to develop and evaluate a machine learning model or diagnose CHD using facial texture features and to compare the performance across different facial regions to provide recommendations for improvement. …”
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A Highly Accurate Adverse Drug Reactions (ADR) Detection from Medical Forum Comments Using Long Short-Term Memory Networks by Anjali Basagodu Veeresh, Ravikumar Guralamata Krishnegowda, Shashikala Salekoppalu Venkataramu

“…Further, the features are converted into LSTM networks to perform the testing operation using the above features. …”
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Para-YOLO: An Efficient High-Parameter Low-Computation Algorithm Based on YOLO11n for Remote Sensing Object Detection by Hang Chen, Qi Cao, Yongqiang Wang, Shang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…By utilizing the intermediate layer of the feature fusion network as the aggregation-diffusion layer, it mitigates the feature degradation caused by consecutive upsampling in Feature Pyramid Networks. …”
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Lightweight Dual-Stream SAR–ATR Framework Based on an Attention Mechanism-Guided Heterogeneous Graph Network by Xuying Xiong, Xinyu Zhang, Weidong Jiang, Tianpeng Liu, Yongxiang Liu, Li Liu

“…Additionally, we include a convolutional neural network based feature extraction net to replenish intuitive visual features. …”
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Ranking Assisted Unsupervised Morphological Disambiguation of Turkish by Hayri Volkan Agun, Ozkan Aslan

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Improving Aerobics Posture Evaluation by Transfer Learning: Humanized Computational Application of BERT-PTA Domain Adaptive Methods by Wenting Zhou, Biao Guo, Feng Cao

“…Second, the BERT-PTA model was used to extract features from the preprocessed posture data. Next, a convolutional neural network was used to construct a key point localization model for aerobics poses, and transfer learning was used to train and fine-tune the model. …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

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Establishment and validation of a combined diagnostic model for aldosterone-producing adenoma of the adrenal gland based on CT radiomics and clinical features by ZHANG Mingquan, LIU Jingjing, LIN Xin, FU Min, FENG Ying, CHEN Jingjing

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The role of learned song in the evolution and speciation of Eastern and Spotted towhees. by Ximena León Du'Mottuchi, Nicole Creanza

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Grading evaluation method for inter-turn short circuit of permanent magnet traction motor based on deep Gaussian processes by DAI Jisheng, HU Dean, XU Hailong, ZHU Wenlong, LIAO Qishu

“…The results show that the proposed method achieves an evaluation accuracy of over 95% under the condition of multi-feature fusion. …”
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Viral evolution sustains a dengue outbreak of enhanced severity by Catherine Inizan, Marine Minier, Matthieu Prot, Olivia O’Connor, Carole Forfait, Sylvie Laumond, Ingrid Marois, Antoine Biron, Ann-Claire Gourinat, Marie-Amélie Goujart, Elodie Descloux, Anavaj Sakuntabhai, Arnaud Tarantola, Etienne Simon-Lorière, Myrielle Dupont-Rouzeyrol

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Evaluation of a fusion model combining deep learning models based on enhanced CT images with radiological and clinical features in distinguishing lipid-poor adrenal adenoma from me... by Shao-Cai Wang, Sheng-Nan Yin, Zi-You Wang, Ning Ding, Yi-Ding Ji, Long Jin

“…Subsequently, multiple machine learning models incorporating clinical and radiological features were developed and evaluated using various indicators and AUC.The best-performing machine learning model was further analyzed using SHAP plots to enhance interpretability and quantify feature contributions. …”
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Nighttime Vehicle Detection Algorithm Based on Improved YOLOv7 by Fan Zhang

“…Second, a lightweight efficient feature fusion network (GS-EFF) is constructed to optimize multi-scale feature alignment by combining the jump connection and GSConv modules to reduce the information loss in the feature fusion process and lower the number of parameters. …”
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The Evolution of the Industrial Specialization of the Radio Electronics Industry of Saint-Petersburg by D. V. Klushantsev

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AFNE-Net: Semantic Segmentation of Remote Sensing Images via Attention-Based Feature Fusion and Neighborhood Feature Enhancement by Ke Li, Hao Ji, Zhijiang Li, Zeyu Cui, Chengkai Liu

“…To address these challenges, this paper proposes AFNE-Net, a general network architecture for remote sensing image segmentation. …”
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