Cross-domain topic transfer learning method based on multiple balance and feature fusion by Zhenshun Xu, Zhenbiao Wang, Wenhao Zhang, Zengjin Tang

“…We propose a novel approach for cross-domain topic transfer learning by combining feature fusion and balancing data and labels. Including applying dual-supervised techniques for handling label dependencies, employing function constraints and data enhancement to adjust data distributions, and utilizing feature fusion techniques to mitigate feature distribution disparities. …”
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Joint Sparse Local Linear Discriminant Analysis for Feature Dimensionality Reduction of Hyperspectral Images by Cong-Yin Cao, Meng-Ting Li, Yang-Jun Deng, Longfei Ren, Yi Liu, Xing-Hui Zhu

“…Although linear discriminant analysis (LDA)-based subspace learning has been widely applied to hyperspectral image (HSI) classification, the existing LDA-based subspace learning methods exhibit several limitations: (1) They are often sensitive to noise and demonstrate weak robustness; (2) these methods ignore the local information inherent in data; and (3) the number of extracted features is restricted by the number of classes. To address these drawbacks, this paper proposes a novel joint sparse local linear discriminant analysis (JSLLDA) method by integrating embedding regression and locality-preserving regularization into the LDA model for feature dimensionality reduction of HSIs. …”
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Network Structure and Core Features of Cognitive Emotion Regulation Strategies in Chinese Adolescents with NSSI by Zhang P, Shi J

“…Targeted interventions should focus on reducing catastrophizing and enhancing positive reappraisal to disrupt these rigid cognitive emotion regulation patterns, ultimately mitigating the risk of NSSI.Keywords: non-suicidal self-injury (NSSI), cognitive emotion regulation strategies (CERS), network analysis, Chinese adolescents…”
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Beyond Traditional Biometrics: Harnessing Chest X-Ray Features for Robust Person Identification by Farah Hazem, Bennour Akram, Tahar Mekhaznia, Fahad Ghabban, Abdullah Alsaeedi, Bhawna Goyal

“…Our methodology is nuanced, employing the potency of Siamese neural networks and the triplet loss in conjunction with refined CNN models for feature extraction. The Siamese networks facilitate robust image similarity comparison, while the triplet loss optimizes the embedding space, mitigating intra-class variations and amplifying inter-class distances. …”
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A stacked ensemble approach to detect cyber attacks based on feature selection techniques by Wahida Ferdose Urmi, Mohammed Nasir Uddin, Md Ashraf Uddin, Md. Alamin Talukder, Md. Rahat Hasan, Souvik Paul, Moumita Chanda, John Ayoade, Ansam Khraisat, Rakib Hossen, Faisal Imran

“…However, the effectiveness of CADS is highly dependent on selecting pertinent features. This research evaluates the impact of three feature selection techniques—Recursive Feature Elimination (RFE), Mutual Information (MI), and Lasso Feature Selection (LFS)—on CADS performance. …”
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Efficient Method for Robust Backdoor Detection and Removal in Feature Space Using Clean Data by Donik Vrsnak, Marko Subasic, Sven Loncaric

“…Using these reconstructed trigger features, the method can be used to efficiently mitigate the effects of an attack. …”
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Adaptive Scattering Feature Awareness and Fusion for Limited Training Data SAR Target Recognition by Chenxi Zhao, Daochang Wang, Xianghui Zhang, Yuli Sun, Siqian Zhang, Gangyao Kuang

“…In addition, a novel azimuth angle-guided classifier is employed to capture the association information between azimuth angle and target features. The physical laws inherent in ESF and azimuth angle guide the network training period, which improves feature discrimination and mitigates the pressure of data inadequacy. …”
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Reinforcement Learning With Deep Features: A Dynamic Approach for Intrusion Detection in IoT Networks by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…Intrusion detection in Internet of Things (IoT) networks is essential to identify and mitigate security breaches and unauthorized access to connected devices. …”
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Urban object detection algorithm based on feature enhancement and progressive dynamic aggregation strategy by Luxuan Bian, Zijun Gao, Jue Wang, Bo Li

“…Second, the adaptive fusion strategy and module facilitate multilevel scale feature fusion, and by dynamically learning fusion weights, they mitigate scale conflicts during the feature extraction process and preserve feature information. …”
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An effective dual encoder network with a feature attention large kernel for building extraction by Shaobo Qiu, Jingchun Zhou, Yuan Liu, Xiangrui Meng

“…Moreover, replacing skip connections with the CTrans module mitigates semantic inconsistency during feature fusion, ensuring better multidimensional feature integration. …”
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Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. by Lingbo Li, Runpu Wang, Miaojie Zou, Fusen Guo, Yuheng Ren

“…Specifically, first, a redundancy-weighted feature fusion module is proposed, enabling the model to fully leverage valuable feature information, thereby improving its performance. …”
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Digital Architectural Form Generation Through Pixel System-Driven Image Feature Information by Hee-Sung An, You-Chang Jeon, Sung-Wook Kim

“…This study analyzes valuable information (image feature information) from pixel-based images to systematize the form generation process utilizing this information. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…It utilizes independent modules to process high- and low-resolution features, adaptively adjusts receptive field sizes, and incorporates dynamic sparse attention mechanisms to optimize feature information at each resolution, by integrating optimal features across multiple scales into density maps for counting evaluation. …”
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The Potential of One-Sided Traditional Windcatchers for Outdoor Use as a Sustainable Urban Feature by Hossein Ghandi, Mattia Federico Leone

“…In urban contexts, turbulence and morphology affect airflow but can be mitigated through regionally tailored windcatcher designs. …”
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Efficient Attention Transformer Network With Self-Similarity Feature Enhancement for Hyperspectral Image Classification by Yuyang Wang, Zhenqiu Shu, Zhengtao Yu

“…Then, we embed these two self-similarity descriptors into the original patch for subsequent feature extraction and classification. Furthermore, we design two efficient feature extraction modules based on the preprocessed patches, called spectral interactive transformer module and spatial conv-attention module, to reduce the computational costs of the classification framework. …”
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Oil Film Detection for Marine Radar Image Using SBR Feature and Adaptive Threshold by Yulong Yang, Jin Yan, Jin Xu, Xinqi Zhong, Yumiao Huang, Jianxun Rui, Min Cheng, Yuanyuan Huang, Yimeng Wang, Tao Liang, Zisen Lin, Peng Liu

“…This paper proposes a marine radar-based oil spill detection method that combines the Significance-to-Boundary Ratio (SBR) feature with an improved Sauvola adaptive thresholding algorithm. …”
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A feature-level ensemble machine learning approach for attack detection in IoT networks by Firoz Khan, B. S. Sunil Kumar, Sangeeta Sangani

“…To address these limitations, this study proposes a feature-level ensemble machine learning approach called Weight-Optimized Extreme Gradient Boosting (WO-XGB). …”
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CB-MTE: Social Bot Detection via Multi-Source Heterogeneous Feature Fusion by Meng Cheng, Yuzhi Xiao, Tao Huang, Chao Lei, Chuang Zhang

“…To mitigate feature redundancy and preserve structural consistency, manifold learning is applied for nonlinear dimensionality reduction, ensuring both local and global topology are maintained. …”
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Margin weighted robust discriminant score for feature selection in imbalanced gene expression classification. by Sheema Gul, Dost Muhammad Khan, Saeed Aldahmani, Zardad Khan

“…To mitigate these issues, customized feature selection methods are required to tackle the class imbalance issue. …”
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TBM Enclosure Rock Grade Prediction Method Based on Multi-Source Feature Fusion by Yong Huang, Xiewen Hu, Shilong Pang, Wei Fu, Shuaipeng Chang, Bin Gao, Weihua Hua

“…Aiming to mitigate engineering risks such as tunnel face collapse and equipment jamming caused by poor geological conditions during the construction of tunnel boring machines (TBMs), this study proposes a TBM surrounding rock grade prediction method based on multi-source feature fusion. …”
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