Visual–Inertial Autonomous UAV Navigation in Complex Illumination and Highly Cluttered Under-Canopy Environments by Leyang Zhao, Weixi Wang, Qizhi He, Li Yan, Xiaoming Li

“…The implementation of UAV autonomous navigation in such environments faces challenges, including dense obstacles, GNSS signal interference, and varying lighting conditions. This paper introduces a UAV autonomous navigation method specifically designed for under-canopy environments. …”
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Research on a Density-Based Clustering Method for Eliminating Inter-Frame Feature Mismatches in Visual SLAM Under Dynamic Scenes by Zhiyong Yang, Kun Zhao, Shengze Yang, Yuhong Xiong, Changjin Zhang, Lielei Deng, Daode Zhang

“…Dynamic feature points interfere with inter-frame motion pose estimation, thereby affecting the accuracy of map construction and the overall robustness of the visual SLAM system. …”
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Functions of Intrinsically Disordered Regions by Linhu Xiao, Kun Xia

“…IDRs harbor molecular recognition features (MoRFs) and post-translational modification sites (e.g., phosphorylation), enabling dynamic intermolecular interactions through conformational plasticity. …”
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A Benchmark Dataset for Aircraft Detection in Optical Remote Sensing Imagery by Jianming Hu, Xiyang Zhi, Bingxian Zhang, Tianjun Shi, Qi Cui, Xiaogang Sun

“…The problem is that existing aircraft detection datasets rarely simultaneously consider the diversity of target features and the complexity of environmental factors, which has become an important factor restricting the effectiveness and reliability of aircraft detection algorithms. …”
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FIDC-YOLO: Improved YOLO for Detecting Pine Wilt Disease in UAV Remote Sensing Images via Feature Interaction and Dependency Capturing by Zekun Xu, Yipeng Zhou, Shiting Wen, Weipeng Jing

“…In addition, the feature aggregation-spatial pyramid pooling fast module is introduced in front of PDC, which aggregates cross-level features to enhance detection performance. …”
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Breast cancer diagnosis with MFF-HistoNet: a multi-modal feature fusion network integrating CNNs and quantum tensor networks by Tariq Mahmood, Tanzila Saba, Amjad Rehman

“…MFF-HistoNet combines a CNN and a Quantum Tensor Network (QTN), which reduces model parameters through parameter compression, enabling deeper global features. The data enhancement method ensures a balanced training set and minimizes color interference. …”
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TSD-Net: A Traffic Sign Detection Network Addressing Insufficient Perception Resolution and Complex Background by Chengcheng Ma, Chang Liu, Litao Deng, Pengfei Xu

“…However, detecting small traffic signs in complex road environments remains a significant challenge due to issues such as low resolution, dense distribution, and visually similar background interference. Existing methods face limitations including high computational cost, inconsistent feature alignment, and insufficient resolution in detection heads. …”
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YOLOv8-SDC: An Improved YOLOv8n-Seg-Based Method for Grafting Feature Detection and Segmentation in Melon Rootstock Seedlings by Lixia Li, Kejian Gong, Zhihao Wang, Tingna Pan, Kai Jiang

“…Furthermore, the incorporated CA mechanism helps the model eliminate background interference for better localization and identification of seedling grafting characteristics. …”
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AMFEF-DETR: An End-to-End Adaptive Multi-Scale Feature Extraction and Fusion Object Detection Network Based on UAV Aerial Images by Sen Wang, Huiping Jiang, Jixiang Yang, Xuan Ma, Jiamin Chen

“…This module uses dual-pathway encoding of high and low frequencies to enhance the focus on the details of dense small targets while reducing noise interference. Additionally, the bidirectional adaptive feature pyramid network (BAFPN) is proposed for cross-scale feature fusion, integrating semantic information and enhancing adaptability. …”
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DSMF-Net: A One-Stage SAR Ship Detection Network Based on Deformable Strip Convolution and Multiscale Feature Refinement and Fusion by Xingyu Liu, Jun Pan, Rong Hu, Wenli Huang, Jiawei Lin, Jiarui Hu

“…To tackle these challenges, we introduce the DSMF-Net, a SAR ship detection network leveraging deformable strip convolution and multiscale feature refinement and fusion. First, to counter interference from complex backgrounds, such as nearshore ports and speckle noise, the deformable strip convolution (DSConv) is introduced and incorporated into the backbone network for SAR ship feature extraction, named SSFEBackbone. …”
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Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method by Lichan Zhou, Jianghui Cai, Haifeng Yang, Ali Luo, Yinbi Li, Chenhui Shi, Boyu Zhang, Jianing Tian, Yinan Yuan, Yuqing Yang

“…This paper provides 7809 carbon star candidates identified from the Large-Area Multi-Object Fiber Optic Spectroscopic Telescope (LAMOST) DR11 and Sloan Digital Sky Survey (SDSS) DR18, using a parallel carbon star feature recognition method. This method deploys a parallel multi-interval feature representation model and a k-nearest neighbor classification model, effectively characterizing local and global molecular bands of carbon stars and enhancing feature discrimination, especially for weak features that are highly susceptible to noise interference. …”
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Screening and Artifact Detection of RFI in Sentinel-1A Time-Series Images Combining Change Detection Techniques With Structural Similarity Index by Zhizheng Zhang, Gaofeng Shu, Yabo Huang, Lin Wu, Ning Li

“…As a wideband radar system, spaceborne synthetic aperture radar (SAR) is susceptible from other high-power radiation sources, which can cause radio frequency interference (RFI) artifacts in the acquired images. …”
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TFC: A Series of Band Selection Methods for Hyperspectral Target Detection by Qianghui Wang, Xikui Miao, Enze Guo, Tao Zhao

“…Based on this idea, a series of BS methods called target feature constrained-based (TFC) used for the field of TD are developed and proposed in this paper. …”
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Staphylococcal enterotoxin-like X (SElX) is a unique superantigen with functional features of two major families of staphylococcal virulence factors. by Ries J Langley, Yi Tian Ting, Fiona Clow, Paul G Young, Fiona J Radcliff, Jeong Min Choi, Richard P Sequeira, Silva Holtfreter, Heather Baker, John D Fraser

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I am Once Again Asking for Your Attention: A Replication of Feature-Based Attention Modulations of Binding Effects with Picture Stimuli by Tarini Singh, Lars-Michael Schöpper, Christian Frings

“…A repetition of any of these features results in a retrieval of the entire episodic trace, and can thus facilitate or interfere with future actions. …”
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Identification of rice leaf disease based on DepMulti-Net by Kui Hu, Kui Hu, Xinying Zheng, Xinying Zheng, Xinyao Su, Lei Wu, Yongmin Liu, Yongmin Liu, Zhenhua Deng

“…This research presents DepMulti-Net, a novel rice disease and pest identification model, designed to overcome the challenges of complex background interference, difficult disease feature extraction, and large model parameter volume in rice leaf disease identification. …”
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Primary Fixation Feature Design Does Not Influence Total Ankle Tibial Component Stability When Implanted with Press-Fit in High Density Bone by Joshua E. Johnson PhD, Gabriel A. Clarke MS, Cesar de Cesar Netto MD, PhD, Donald D. Anderson PhD

“…Implant positioning and interference fit (100 µm) were set according to surgical guidelines (Fig. 1A). …”
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DRST-Net: A Dual-Branch Feature Fusion Network Combining ResNet50 and Swin Transformer for Welding Light Strip Recognition by Yuan Lu, Qingjiu Huang

“…To address the challenges of strong arc light noise, metal spatter, and smoke interference in weld seam recognition, we propose DRST-Net, a dual-branch cross-attention feature fusion network. …”
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An Underwater Acoustic Communication Signal Modulation-Style Recognition Algorithm Based on Dual-Feature Fusion and ResNet–Transformer Dual-Model Fusion by Fanyu Zhou, Haoran Wu, Zhibin Yue, Han Li

“…This paper proposes a dual-feature ResNet–Transformer model with two innovative breakthroughs: (1) A dual-modal fusion architecture of ResNet and Transformer is constructed using residual connections to alleviate gradient degradation in deep networks and combining multi-head self-attention to enhance long-distance dependency modeling. (2) The time–frequency representation obtained from the smooth pseudo-Wigner–Ville distribution is used as the first input branch, and higher-order statistics are introduced as the second input branch to enhance phase feature extraction and cope with channel interference. …”
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A lithium-ion batteries SOH estimation method based on extracting new features during the constant voltage charging stage and improving BPNN. by Yanhua Xian, Mingyang Li, Jiayin Huang

“…The complexity and noise interference of battery data make it difficult to accurately extract health features, and it is necessary to develop effective methods to process the data and extract representative features. …”
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