Degradation Prediction of Proton Exchange Membrane Fuel Cell Based on Multi-Head Attention Neural Network and Transformer Model by Yikai Tang, Xing Huang, Yanju Li, Haoran Ma, Kai Zhang, Ke Song

“…After this input simplification, the model still maintained a prediction accuracy comparable to that of the full-feature model. …”
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Transcranial Direct Current Stimulation-Based Neuromodulation Improves the Performance of Brain–Computer Interfaces Based on Steady-State Visual Evoked Potential by Shangen Zhang, Xiaorong Gao, Hongyan Cui, Xiaogang Chen

“…The findings of this study provide insights into the improvement of BCI performance based on personal state interventions and provide an objective method for quantitative brain state monitoring that may be used for EEG modeling of SSVEP-BCIs.…”
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WCANet: An Efficient and Lightweight Weight Coordinated Adaptive Detection Network for UAV Inspection of Transmission Line Accessories by Jiawei Chen, Pengfei Shi, Mengyao Xu, Yuanxue Xin, Xinnan Fan, Jinbo Zhang

“…Compared with other methods, our WCANet achieves highly accurate prediction of high-voltage transmission accessories with fewer parameters and model sizes, availably balancing model performance and complexity.…”
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Identifying key genetic variants in Alzheimer’s disease progression using Graph Convolutional Networks (GCN) and biological impact analysis by Belal A. Hamed, Heba Mamdouh Farghaly, Ahmed Omar, Tarek Abd El-Hafeez

“…Using rigorously curated data from the GWAS Catalog and AD-specific functional networks (FGN), the model achieved exceptional performance (accuracy: 98.04 ± 0.32%, AUROC: 0.996). …”
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Application of machine learning techniques to predict the compressive strength of steel fiber reinforced concrete by Ala’a R. Al-Shamasneh, Arsalan Mahmoodzadeh, Faten Khalid Karim, Taoufik Saidani, Abdulaziz Alghamdi, Jasim Alnahas, Mohammed Sulaiman

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A Novel Low-Rank Embedded Latent Multi-View Subspace Clustering Approach by Sen Wang, Lian Chen, Zhijian Liang, Qingyang Liu

“…To alleviate these issues, we present a latent multi-view representation learning model based on low-rank embedding by implicitly uncovering the latent consistency structure of data, which allows us to achieve robust and efficient multi-view feature fusion. …”
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FD-IDS: Federated Learning with Knowledge Distillation for Intrusion Detection in Non-IID IoT Environments by Haonan Peng, Chunming Wu, Yanfeng Xiao

“…Together, these mechanisms effectively alleviate the problem of model drift. Experiments conducted on both the Edge-IIoT and N-BaIoT datasets demonstrate that FD-IDS achieves promising detection performance across multiple evaluation metrics.…”
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A comprehensive diagnostic framework for hepatitis C using structured data and predictive analytics by Behnaz Motamedi, Balázs Villányi

“…Although ML presents opportunities for stage prediction, issues such as class imbalance, missing data, and feature redundancy limit model efficacy and generalizability. …”
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Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective... by Seok Jun Park, Seungwon Yang, Suhyun Lee, Sung Hwan Joo, Taemin Park, Dong Hyun Kim, Hyeonji Kim, Soyun Park, Jung-Tae Kim, Won Gun Kwack, Sung Wook Kang, Yun-Kyoung Song, Jae Myung Cha, Sang Youl Rhee, Eun Kyoung Chung

“…The full ML models were then simplified by selecting critical features based on the feature importance values (FIVs). …”
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OFPoint: Real-Time Keypoint Detection for Optical Flow Tracking in Visual Odometry by Yifei Wang, Libo Sun, Wenhu Qin

“…We use the descriptor-based detector simple learned keypoints (SiLK) as the pre-trained model and fine-tune it to avoid training from scratch. …”
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BCS_YOLO: Research on Corn Leaf Disease and Pest Detection Based on YOLOv11n by Shengnan Hao, Erjian Gao, Zhanlin Ji, Ivan Ganchev

“…Traditional manual detection methods suffer from significant limitations in both performance and efficiency. To address this, the present paper proposes a novel biotic condition screening (BCS) model for the detection of corn leaf diseases and pests, called BCS_YOLO, based on the You Only Look Once version 11n (YOLOv11n). …”
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RCLT-Net: An Indoor Panoramic Room Layout Estimation Framework Based on Consecutive Dilated Convolutions and Transformer by Qiucheng Sun, Zhengkai Deng, Jinlong Zhu

“…This design enhances the perception of fine-grained multi-scale features. Additionally, we introduce the Local-Global Feature Interaction Shifting Window Transformer, which significantly improves the Transformer model’s ability to extract features by fostering robust interactions between local and global features, enabling more flexible and efficient feature representation. …”
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LE-YOLO: A Lightweight and Enhanced Algorithm for Detecting Surface Defects on Particleboard by Chao He, Yongkang Kang, Anning Ding, Wei Jia, Huaqiong Duo

“…A lightweight detection head was further designed, integrating shared convolutional operations with a distribution-aware loss function, thereby substantially improving detection performance in complex textured environments. Experimental evaluations conducted on the Chipboardv1.0 particleboard surface defect dataset demonstrated that compared to the baseline YOLOv11n model, LE-YOLO achieved a 5% improvement in recall, a 1% increase in F1 score, a 4% enhancement in mAP@50, a 6% gain in mAP@50–95, a 12.69% acceleration in inference speed, and an 18.6% reduction in parameter count. …”
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Partial Discharge Pattern Recognition of Switchgear Based on Residual Convolutional Neural Network by Xueyou HUANG, Jun XIONG, Yu ZHANG, Hui LIU, Lu CHEN, Xianglin MENG, Xiuchen JIANG

“…Through integrated use of the feature layer fusion module and residual module, the proposed model is significantly improved in the generalization performance and is more suitable for practical engineering.…”
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ACT-FRCNN: Progress Towards Transformer-Based Object Detection by Sukana Zulfqar, Zenab Elgamal, Muhammad Azam Zia, Abdul Razzaq, Sami Ullah, Hussain Dawood

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TCCFNet: a semantic segmentation method for mangrove remote sensing images based on two-channel cross-fusion networks by Lixiang Fu, Yaoru Wang, Shulei Wu, Jiasen Zhuang, Zhongqiang Wu, Jian Wu, Huandong Chen, Yukai Chen

“…This study introduces a dual-backbone network architecture that combines ResNet for fine-grained local feature extraction and Swin Transformer for global context modeling. …”
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AI Knows Aesthetics: AI-Generated Interior Design Identification Using Deep Learning Algorithms by Fei Liu, Kailing Deng

“…By leveraging a proprietary dataset composed of diverse AI-generated and real-world interior designs, our model achieved a peak classification accuracy of 97%, demonstrating superior performance compared to traditional deep learning techniques. …”
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Cross modal recipe retrieval with fine grained modal interaction by Fan Zhao, Yuqing Lu, Zhuo Yao, Fangying Qu

“…Utilizing the similarity between image local features and intermediate recipe representations, TCVE enhances visual representation by deeper model relearning. …”
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Damage identification based on the inner product matrix and parallel convolution neural network for frame structure by Yingying He, Ji Feng, Baogang Sun, Feixue Wang, Likai Zhang, Jidi Jiang

“…The results demonstrate that the IPM-PCNN model can automatically extract relevant features from the signals to accurately identify structural damage, achieving an accuracy of 96.60% on the test set, outperforming machine learning methods in performance. …”
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Multimodal medical image fusion combining saliency perception and generative adversarial network by Mohammed Albekairi, Mohamed vall O. Mohamed, Khaled Kaaniche, Ghulam Abbas, Meshari D. Alanazi, Turki M. Alanazi, Ahmed Emara

“…The TDN architecture incorporates two key components: a salient perception model for discriminative feature extraction and a generative adversarial network for temporal feature matching. …”
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