An efficient method for identifying surface damage in hydraulic concrete buildings by Libo Yang, Dawei Zhu, Xuemei Liu

“…This paper proposes an efficacious methodology for identifying diverse apparent damages in hydraulic structures to address the limitations of existing technologies. The advanced features of apparent damage in hydraulic structures were elucidated by fine-tuning the top-level parameters of the lightweight pre-trained model, thereby mitigating the data dependency issue inherent in the model. …”
Get full text

MFFNet: a building change detection method based on fusion of spectral and geometric information by Zhihao Guo, Jianping Pan, Peng Xie, Ling Zhu, Chen Qi, Xunxun Wang, Yihan Yang, Yan Wang, Huijuan Zhang, Zhaohui Ren

“…It takes multiscale features and establishes relationships between neighbouring pixels using the pixel-shuffle algorithm, then fuses and reorganizes the multiscale features to highlight the relationships between global contexts, thereby mitigating the problem of building occlusion by shadows. …”
Get full text

Evaluating machine leaning algorithms for accuracy, stability, and among-predictors discriminability in modeling species-richness across ten datasets by Yong Cao, Tyler E. Schartel, David C. Houghton, Jared Ross, Dana M. Infante

Get full text

Assessing relative contributions of climate and socio-environmental factors to ecosystem health through space–time interpretable machine learning by Xiaoliang Meng, Junyi Wu, Yichun Xie, Yongfei Bai, Chenghu Zhou, Yuchen Li

“…The IML models support the concurrent spatiotemporal examination of ecosystem health and feature engineering to mitigate limitations from multicollinearity and non-linearity. …”
Get full text

Image processing‐based noise‐resilient insulator defect detection using YOLOv8x by Shagor Hasan, Md. Abdur Rahman, Md. Rashidul Islam, Animesh Sarkar Tusher

Get full text

Lithology classification integrating multi-source remote sensing data after vegetation suppression: a case study from Inner Mongolia Autonomous Region, China by Jiaxin Lu, Ling Han, Junfeng Wang, Liangzhi Li, Zhaode Xia

“…Subsequently, a 63-dimensional feature sequence was extracted from the vegetation-suppressed images. …”
Get full text

A prior-knowledge-guided dynamic attention mechanism to predict nocturnal hypoglycemic events in type 1 diabetes by Xia Yu, Zi Yang, Xinzhuo Wang, Xiaoyu Sun, Ruiting Shen, Hongru Li, Mingchen Zhang

“…By integrating our proposed framework into the nocturnal hypoglycemia early warning model, issues related to feature redundancy and incompleteness were mitigated. …”
Get full text

MSFUnet: A Semantic Segmentation Network for Crop Leaf Growth Status Monitoring by Zhihan Cheng, He Yan

“…MSFUnet integrates a multi-path feature fusion (MFF) mechanism and an edge-detail focus (EDF) module. …”
Get full text

ATT-CR: Adaptive Triangular Transformer for Cloud Removal by Yang Wu, Ye Deng, Pengna Li, Wenli Huang, Kangyi Wu, Xiaomeng Xin, Jinjun Wang

“…To address these challenges, we propose the adaptive triangular transformer for cloud removal (ATT-CR), a model that effectively reduces computational costs and mitigates interference from cloudy pixels. Specifically, it consists of two core components: Triangular attention (TAN) and feature selected gating module (FSGM). …”
Get full text

Autism Identification Based on the Intelligent Analysis of Facial Behaviors: An Approach Combining Coarse- and Fine-Grained Analysis by Jingying Chen, Chang Chen, Ruyi Xu, Leyuan Liu

“…Conclusions: This experimental result underscores the improved generalizability of facial behavior features and effectively mitigates the complexities stemming from the pronounced intragroup variability of those with autism, thereby contributing to more accurate and interpretable autism identification.…”
Get full text

Advanced Multi-Level Ensemble Learning Approaches for Comprehensive Sperm Morphology Assessment by Abdulsamet Aktas, Taha Cap, Gorkem Serbes, Hamza Osman Ilhan, Hakkı Uzun

“…<b>Methods:</b> We propose a novel ensemble-based classification approach that combines convolutional neural network (CNN)-derived features using both feature-level and decision-level fusion techniques. …”
Get full text

An improved lightweight tongue segmentation model with self-attention parallel network and progressive upsampling by Xuan Wang, Yifang Cao, Yijia Chen, Huixia Li, Aiqing Han, Yan Tang

“…The model incorporates three key enhancements: (1) the adoption of a Self-Attention Parallel Network that integrates the self-attention mechanism and residual modules to achieve simultaneous extraction of local and global features; (2) the integration of the Efficient Channel Attention(ECA) mechanism into the Mix-FFN component to enhance feature extraction efficiency; and (3) the utilization of Multi-dimensional Feature Progressive Upsampling to mitigate precision loss during the upsampling process. …”
Get full text

LFN-YOLO: precision underwater small object detection via a lightweight reparameterized approach by Mingxin Liu, Mingxin Liu, Yujie Wu, Ruixin Li, Cong Lin, Cong Lin

“…Then, we replaced the standard depthwise convolution in the feature extraction network with SPD-Conv, which includes an additional pooling layer to mitigate detail loss. …”
Get full text

Attention-driven hybrid deep learning and SVM model for early Alzheimer’s diagnosis using neuroimaging fusion by Arjun Kidavunil Paduvilan, Godlin Atlas Lawrence Livingston, Sampath Kumar Kuppuchamy, Rajesh Kumar Dhanaraj, Muthuvel Subramanian, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

“…Deep learning models extract high-level imaging features which are then concatenated with SVM kernels in a late-fusion ensemble. …”
Get full text

A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…The DNN framework significantly mitigates coastal salinity biases caused by RFI and land contamination, providing a robust tool for applications such as coastal hydrological monitoring and marine resource management.…”
Get full text

Using Machine Learning Algorithms in Intrusion Detection Systems: A Review by Mazin S. Mohammed, Hasanien Ali Talib

“… Intrusion Detection Systems (IDS) are essential for identifying and mitigating security threats in Internet of Things (IoT) networks. …”
Get full text

Enhanced CO₂ Emissions Prediction Using Temporal Fusion Transformer Optimized by Football Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally

“…However, challenges such as high-dimensional feature spaces, feature redundancy, and hyperparameter sensitivity limit the efficiency of machine learning (ML) models in CO₂ emissions forecasting. …”
Get full text

Chronic lymphocytic leukemia (CLL) screening and abnormality detection based on multi-layer fluorescence imaging signal enhancement and compensation by Lemin Shi, Ping Gong, Mingye Li, Dianxin Song, Hao Zhang, Zhe Wang, Xin Feng

“…Conclusion Visual analysis demonstrated clearer, more continuous, and uniform fluorescence signals, effectively mitigating fragmentation and uneven distribution. These improvements reduced false negatives and enhanced genomic abnormality detection accuracy. …”
Get full text

KGRDR: a deep learning model based on knowledge graph and graph regularized integration for drug repositioning by Huimin Luo, Huimin Luo, Hui Yang, Hui Yang, Ge Zhang, Ge Zhang, Jianlin Wang, Jianlin Wang, Junwei Luo, Chaokun Yan, Chaokun Yan, Chaokun Yan

“…Next, the similarity features and topological features are fused by utilizing an attention-based feature fusion method. …”
Get full text

SAM2-DFBCNet: A Camouflaged Object Detection Network Based on the Heira Architecture of SAM2 by Cao Yuan, Libang Liu, Yaqin Li, Jianxiang Li

“…Our network incorporates three key modules: (1) the Camouflage-Aware Context Enhancement Module (CACEM), which fuses local and global features through an attention mechanism to enhance contextual awareness in low-contrast scenes; (2) the Cross-Scale Feature Interaction Bridge (CSFIB), which employs a bidirectional convolutional GRU for the dynamic fusion of multi-scale features, effectively mitigating representation inconsistencies caused by complex textures and deformations; and (3) the Dynamic Boundary Refinement Module (DBRM), which combines channel and spatial attention mechanisms to optimize boundary localization accuracy and enhance segmentation details. …”
Get full text