Uncovering the Web of Secrets Surrounding Employee Monitoring Software: A Content Analysis of Information Provided by Vendors by Felicia Laksanadjaja, Oscar Oviedo-Trespalacios

“…The findings show that risk-mitigating features are uncommon in the solutions offered by these companies. …”
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Mitigating Multicollinearity in Induction Motors Fault Diagnosis Through Hierarchical Clustering-Based Feature Selection by Bassam A. Hemade, Sabbah Ataya, Attia A. El-Fergany, Nader M. A. Ibrahim

“…A novel feature selection approach based on agglomerative hierarchical clustering (AHC) is proposed to mitigate feature redundancy and enhance model generalization. …”
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A Novel Wood Surface Defect Detection Model Based on Improved YOLOv8 by Wenmiao Dou, Jun You

“…A learnable dynamic upsampling module replaces traditional nearest-neighbor interpolation to mitigate feature loss during resolution recovery. Additionally, a structural Re-parameterizable Block is adopted to enhance feature expressiveness during inference, and a small-object detection head is added to enhance the detection of small defects while minimizing both missed and incorrect detections. …”
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Feature Transformation-Based Few-Shot Class-Incremental Learning by Xubo Zhang, Yang Luo

“…To address this issue, this paper proposes a feature transformation method that mitigates feature degradation in few-shot incremental learning. …”
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Designing digital conversational agents for youth with multiple mental health conditions: Insights on key features from a youth-engaged qualitative descriptive study by Jingyi Hou, Jamie Gibson, Thalia Phi, Brian Ritchie, Louise Gallagher, Gillian Strudwick, George Foussias, Darren B Courtney, Aristotle Voineskos, Stephanie Ameis, Kristin Cleverley, Lisa D Hawke

“…Results Four key themes were generated from the focus group data: (1) the importance of a customizable and flexible design for personalization; (2) confidentiality, privacy features and risk mitigation features; (3) the need for reliable, informative content that is user tested and validated; (4) a friendly and human-like interaction style. …”
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(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…In multi-class attack identification scenarios, the framework mitigates feature confusion between rare attacks (e.g., user-to-root attacks) and normal traffic through adaptive feature weight allocation. …”
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Improved method for a pedestrian detection model based on YOLO by Yanfei LI, Chengyi DONG

“…The main innovations were: (1) integration of spatial pyramid dilated (SPD) operations with conventional convolution layers to construct SPD-Conv modules, which effectively mitigated feature information loss while enhancing small-target detection accuracy; (2) incorporation of selective kernel attention mechanisms to enable context-aware feature selection and adaptive feature extraction. …”
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A Novel Swin-Transformer with Multi-Source Information Fusion for Online Cross-Domain Bearing RUL Prediction by Zaimi Xie, Chunmei Mo, Baozhu Jia

“…A self-attention mechanism further integrates multi-source features, while an adversarial Multi-Kernel Maximum Mean Discrepancy (MK-MMD) combined with a relational network mitigates feature distribution differences across domains. …”
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Cross-domain topic transfer learning method based on multiple balance and feature fusion by Zhenshun Xu, Zhenbiao Wang, Wenhao Zhang, Zengjin Tang

“…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. Additionally, we introduce a topic knowledge distillation method, leveraging topics from the source domain to guide and optimize topic generation in the target domain. …”
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Accurately Identifying Different Ripening Stages of Strawberry Fruits in Complex Agricultural Scenarios by Xuefeng Ren, Yang Gan, Huan Liu, Yongming Chen, Ping Lin

“…Simultaneously, self-calibrated convolutions are integrated to leverage spatial and channel reconstruction units, effectively mitigating feature redundancy across spatial and channel dimensions. …”
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VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

“…Second, the YOLOv8 network’s Spatial Pyramid Pooling Fast (SPPF) module is replaced with a novel Feature Pyramid Convolution Fast (FPCF) module based on dilated convolution, effectively mitigating feature loss in small target processing. Additionally, a lightweight Optimized Shared Detection Head (OSDH-Head) is introduced, reducing computational complexity while improving detection efficiency. …”
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High-Accuracy Recognition Method for Diseased Chicken Feces Based on Image and Text Information Fusion by Duanli Yang, Zishang Tian, Jianzhong Xi, Hui Chen, Erdong Sun, Lianzeng Wang

“…Key innovations include the following: (1) Integrating MASA(Manhattan self-attention)and DSconv (Depthwise Separable convolution) into the backbone network to mitigate feature confusion. (2) Utilizing a pre-trained BERT to extract textual semantic features, reducing annotation dependency and cost. (3) Designing a lightweight Gated Cross-Attention (GCA) module for dynamic multimodal fusion, achieving a 41% parameter reduction versus cross-modal transformers. …”
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Enhancing Neural Network Interpretability Through Deep Prior-Guided Expected Gradients by Su-Ying Guo, Xiu-Jun Gong

“…This approach not only mitigates feature absence artifacts but also amplifies critical feature contributions through adaptive gradient aggregation. …”
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A novel multimodel medical image fusion framework with edge enhancement and cross-scale transformer by Fei Luo, Daoqi Wu, Luis Rojas Pino, Weichao Ding

“…Additionally, a multi-path fusion strategy is introduced to disentangle deep and shallow features, mitigating feature loss during fusion. We conduct extensive experiments on the AANLIB dataset, evaluating CT-MRI, PET-MRI, and SPECT-MRI fusion tasks. …”
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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

“…CB-MTE adopts a hierarchical architecture: user metadata is used to construct behavioral portraits, deep semantic representations are extracted from textual content via DistilBERT, and community-aware graph embeddings are learned through a combination of random walk and Skip-gram modeling. 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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GPR-TSBiNet: An Information Gradient Enrichment Model for GPR B-Scan Small Target Detection by Chongqin Wang, Yi Guan, Minghe Chi, Feng Shen, Zhilong Yu, Qingguo Chen, Chao Chen

“…In the neck stage, we develop the Spatial-Depth Converted Bidirectional Feature Pyramid Network (SC-BiFPN), which integrates SPD-ADown to mitigate feature loss caused by traditional pooling-based downsampling. …”
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Learnable Resized and Laplacian-Filtered U-Net: Better Road Marking Extraction and Classification on Sparse-Point-Cloud-Derived Imagery by Miguel Luis Rivera Lagahit, Xin Liu, Haoyi Xiu, Taehoon Kim, Kyoung-Sook Kim, Masashi Matsuoka

“…Addressing this, we propose improving U-Net’s ability to extract and classify road markings from sparse-point-cloud-derived images by introducing a learnable resizer (LR) at the input stage and learnable resizer blocks (LRBs) throughout the network, thereby mitigating feature and localization degradation from resizing operations in the deep learning framework. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…To address these challenges, we propose a lightweight SAR small ship detection network, LWSARDet, which mitigates feature redundancy and reduces computational complexity in existing models. …”
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GCOANet: A gradient consistency constraints semi-supervised network for optical image-assisted SAR despeckling by Yang Yang, Jun Pan, Jiangong Xu, Zhongli Fan, Zeming Geng, Junli Li

“…The presented method generates cross-domain reference images by utilizing optical pixel correlation to conduct the paired SAR reconstruction, thereby mitigating feature misalignment caused by the modal differences between SAR and optical imagery. …”
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FVPNet: A Fuzzy Visual Positioning Perception Network for Small Object Segmentation in Remote Sensing Images by Yu Yan, Jindong Xu, Qianpeng Chong, Guangyi Wei, Zhixiang Wang

“…The FID module integrates diverse feature map extraction techniques to construct a more robust feature map through various subsampling methods, mitigating feature loss in foreground targets. The FR subnet employs high-order fuzzy modeling with adaptive membership functions and a constrained-space boundary adaptation strategy to address boundary uncertainty in RSIs. …”
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