Abnormal Sound Detection of Wind Turbine Gearboxes Based on Improved MobileFaceNet and Feature Fusion by Yuelong Liang, Haorui Liu, Yayu Chen

“…To solve problems such as the unstable detection performance of the sound anomaly detection of wind turbine gearboxes when only normal data are used for training, and the poor detection performance caused by the poor classification of samples with high similarity, this paper proposes a self-supervised wind turbine gearbox sound anomaly detection algorithm that fuses time-domain features and Mel spectrograms, improves the MobileFaceNet (MFN) model, and combines the Gaussian Mixture Model (GMM). …”
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Automatic Extraction of Water Body from SAR Images Considering Enhanced Feature Fusion and Noise Suppression by Meijun Gao, Wenjie Dong, Lifu Chen, Zhongwu Wu

“…Though great progress has been achieved, there are still some challenges, such as an insufficient ability to extract water edge details, an inability to detect small water bodies, and a weak ability to suppress background noise. To address these problems, we propose the Global Context Attention Feature Fusion Network (GCAFF-Net) in this article. …”
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Improved YOLOv8 Network of Aircraft Target Recognition Based on Synthetic Aperture Radar Imaging Feature by Xing Wang, Wen Hong, Yunqing Liu, Guanyu Yan, Dongmei Hu, Qi Jing

“…The grayscale images of passenger aircraft targets obtained via Synthetic Aperture Radar (SAR) have problems such as complex airport backgrounds, significant speckle noise, and variable scales of targets. …”
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Autonomous Aerial Vehicle Object Detection Based on Spatial Perception and Multiscale Semantic and Detail Feature Fusion by Wei Rao, Siyuan Chen, Dan Li

“…Second, to improve the detection performance of DyHead and make the model lightweight, a new feature pyramid network (SDI-MBiFPN) in the Neck of YOLOv8s is proposed, which contains a Multiscale Bidirectional Feature Pyramid Network (BiFPN), called MBiFPN, and a feature fusion method based on the redesigned Semantic and Detail Fusion (SDI). …”
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Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation by Jungpil Shin, Abu Saleh Musa Miah, Rei Egawa, Koki Hirooka, Md. Al Mehedi Hasan, Yoichi Tomioka, Yong Seok Hwang

“…In response to these challenges, this paper proposes a novel three-stream spatio-temporal feature-based human fall detection system. Our system incorporates joint skeleton-based spatial and temporal Graph Convolutional Network (GCN) features, joint motion-based spatial and temporal GCN features, and residual connections-based features. …”
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Toward Efficient UAV-Based Small Object Detection: A Lightweight Network with Enhanced Feature Fusion by Xingyu Di, Kangning Cui, Rui-Feng Wang

“…Firstly, a double separation convolution (DSC) module is designed to replace the Bottleneck structure in the C2f module with deep separable convolution and point-by-point convolution fusion, which can reduce the model parameters and calculation complexity while enhancing feature expression. Secondly, a new SPPL module is proposed, which combines spatial pyramid pooling rapid fusion (SPPF) with long-distance dependency modeling (LSKA) to improve the robustness of the model to multi-scale targets through cross-level feature association. …”
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Geometric Detail-Preserved Point Cloud Upsampling via a Feature Enhanced Self-Supervised Network by Shengwei Qin, Yao Jin, Hailong Hu

“…., corner or edge points) and producing points gathered together. These problems are caused by similar feature replication or insufficient supervised information. …”
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Family Physicians’ Feedback on the Feature Design of a Digital Health Platform to Streamline the Care of Older Adults by Marjan Abbasi, Sheny Khera, Julia Dabravolskaj, Amira Aissiou, Reza Abbasi-Dezfouly

“…Digital health tools offer potential solutions to these problems. This study examined the interface design and features of a digital health platform, Carmi, designed to mitigate administrative inefficiencies and cognitive overload by asynchronous patient data gathering and automated report generation. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…The spatial information of the channels is compressed by global average pooling, and the feature map is adaptively weighted after learning the channel weights through the fully connected layer, so as to strengthen the key channel features and suppress the noise. …”
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A combined feature selection approach for malicious email detection based on a comprehensive email dataset by Han Zhang, Yong Shi, Ming Liu, Libo Chen, Songyang Wu, Zhi Xue

“…Furthermore, we propose a new feature selection and construction method that combines both static features and textual features. …”
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Multi-scale cross-layer fusion and center position network for pedestrian detection by Qian Liu, Youwei Qi, Cunbao Wang

“…A new backbone unit is designed to introduce channel-wise attention into the improved aggregated residual transformations for effective feature extraction. We select suitable anchor setting for pedestrian detection datasets to tackle the problem of dataset difference. …”
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Unpaired Spatio-Temporal Fusion for Remote Sensing Images via Deformable Global-Local Feature Alignment by Xinlan Ding, Huihui Song, Xu Zhang

“…., from the land to the water), which makes it difficult to obtain enough high-quality reference data, leading to severe model degradation. To solve the above problems, we propose the deformable global-local feature alignment network (DGFANet) for unpaired spatio-temporal fusion, which combines convolutional neural network and transformer to enhance texture and semantic details through global-local alignment. …”
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A Lightweight Intrusion Detection System with Dynamic Feature Fusion Federated Learning for Vehicular Network Security by Junjun Li, Yanyan Ma, Jiahui Bai, Congming Chen, Tingting Xu, Chi Ding

“…The traditional Intrusion Detection System (IDS) makes it difficult to effectively deal with the dynamics and complexity of emerging threats. To solve these problems, a lightweight vehicular network intrusion detection framework based on Dynamic Feature Fusion Federated Learning (DFF-FL) is proposed. …”
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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…This study explores the use of transfer learning, where information learned from another, and often much larger, dataset is used to potentially reduce the need for a large, problem-specific training dataset. Two anthropogenic geomorphic feature extraction problems are explored: the extraction of agricultural terraces and the mapping of surface coal mine reclamation-related valley fill faces. …”
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Model Klasifikasi Dengan Logistic Regression Dan Recursive Feature Elimination Pada Data Tidak Seimbang by Sutarman, Rimbun Siringoringo, Dedy Arisandi, Edi Kurniawan, Erna Budhiarti Nababan

“…Logistic regression can yield good results in classification and prediction problems. The extensive features of the dataset can lead to computational burdens and reduced classification performance. …”
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Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

“…Traditional weld seam detection methods include destructive testing and non-destructive testing; however, destructive testing has high costs and long cycles, and non-destructive testing, such as radiographic testing and ultrasonic testing, also have problems such as high consumable costs, slow detection speed, or high requirements for operator experience. …”
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A knowledge graph attention network for the cold‐start problem in intelligent manufacturing: Interpretability and accuracy improvement by Ziye Zhou, Yuqi Zhang, Shuize Wang, David San Martin, Yongqian Liu, Yang Liu, Chenchong Wang, Wei Xu

“…Additionally, we employ the Integrated Gradients (IG) method to shed light on the model's predictions, revealing the relative importance of each feature within the knowledge graph. Notably, this work represents the first application of knowledge graph attention neural networks to address the cold‐start problem in steel rolling production. …”
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Machine learning algorithm for intelligent detection of WebShell by Hua DAI, Jing LI, Xin-dai LU, Xin SUN

“…WebShell is a common tool for network intrusions,which has the characteristics of great harm and good concealment.The current detection method is relatively simple,and easy to be bypassed,so it is difficult to deal with complex and flexible WebShell.To solve these problems,a supervised machine learning algorithm was put forward to detect WebShell intelligently.By learning the features of existing WebShell and non-existing WebShell pages,the algorithm can make prediction of the unknown pages,and the flexibility and adaptability were both very good.Compared with the traditional WebShell detection methods,the experiment proves that the algorithm has higher detection efficiency and accuracy,and at the same time there is a certain probability to detect new types of WebShell.…”
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Impulse Control Problems Following Bariatric Surgery and Extrapyramidal Adverse Effects with Fluoxetine: A Case Report by Ayşe Gökçen Gündoğmuş, Kübra Sezer Katar

“…Especially when surgery is used in patients with eating disorders, different addiction problems and impulse control disorders may arise afterward. …”
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Existence of Solutions for a Perturbed <i>N</i>-Laplacian Boundary Value Problem with Critical Growth by Sheng Shi, Yang Yang

“…This is achieved by employing a combination of the Trudinger–Moser-type inequality and a linking theorem based on the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi mathvariant="double-struck">Z</mi><mn>2</mn></msub></semantics></math></inline-formula>-cohomological index. The main feature and novelty of this paper lies in extending the equation to <i>N</i>-Laplacian boundary value problems utilizing the aforementioned methods. …”
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