MASNet: mixed attention Siamese network for visual object tracking by Jianwei Zhang, Zhichen Zhang, Huanlong Zhang, Jingchao Wang, He Wang, Menya Zheng

“…However, the correlation operation directly uses the template feature to slide the window on the search area feature, and it is difficult to distinguish the target and background information when encountering similar target interference and background clutter, which can easily lead to tracking failure. …”
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FFAE-UNet: An Efficient Pear Leaf Disease Segmentation Network Based on U-Shaped Architecture by Wenyu Wang, Jie Ding, Xin Shu, Wenwen Xu, Yunzhi Wu

“…The AGM module effectively suppresses background noise interference by reconstructing features and accurately capturing spatial and channel relationships, while the FESM module enhances the model’s responsiveness to disease features at different scales through channel aggregation and feature supplementation mechanisms. …”
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Gesture Recognition Achieved by Utilizing LoRa Signals and Deep Learning by Peihao Zhang, Baofeng Zhao

“…To counter environmental noise and static interferences, an adaptive segmentation approach based on sliding window variance analysis is introduced in the research. …”
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Dynamic Observation of Ultrashort Pulses with Chaotic Features in a Tm-Doped Fiber Laser with a Single Mode Fiber–Grade Index Multimode Fiber–Single Mode Fiber Structure by Zhenhong Wang, Zexin Zhou, Yubo Ji, Qiong Zeng, Yufeng Song, Geguo Du, Hongye Li

“…In this study, we have demonstrated an ultrafast Tm-doped fiber laser utilizing the nonlinear multimode interference (NL-MMI) effect, with a single mode fiber–grade index multimode fiber–single mode fiber (SMF-GIMF-SMF) structure serving as the saturable absorber (SA). …”
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IDDNet: Infrared Object Detection Network Based on Multi-Scale Fusion Dehazing by Shizun Sun, Shuo Han, Junwei Xu, Jie Zhao, Ziyu Xu, Lingjie Li, Zhaoming Han, Bo Mo

“…IDDNet includes a multi-scale fusion dehazing (MSFD) module, which uses multi-scale feature fusion to eliminate haze interference while preserving key object details. …”
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ALPD-Net: a wild licorice detection network based on UAV imagery by Jing Yang, Huaibin Qin, Jianguo Dai, Guoshun Zhang, Miaomiao Xu, Yuan Qin, Jinglong Liu

“…Through adaptive channel space and positional encoding, background interference is effectively suppressed. Additionally, to enhance the model’s attention to licorice at different scales, a Lightweight Multi-Scale Module (LMSM) using multi-scale dilated convolution is introduced, significantly reducing the probability of missed detections. …”
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An improved EAE-DETR model for defect detection of server motherboard by Jian Chi, Mingke Zhang, Puhon Zhang, Guowang Niu, Zhihao Zheng

“…Subsequently, we introduced the AIFI-ASSA module, designed to mitigate background noise interference and improve sensitivity to minor defects by employing an adaptive sparse self-attention mechanism. …”
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Research Progress on Modulation Format Recognition Technology for Visible Light Communication by Shengbang Zhou, Weichang Du, Chuanqi Li, Shutian Liu, Ruiqi Li

“…This paper systematically reviews the research progress in MFR for VLC, comparing the theoretical frameworks and limitations of traditional likelihood-based (LB) and feature-based (FB) methods. It also explores the advancements brought by deep learning (DL) technology, particularly in enhancing noise robustness, classification accuracy, and cross-scenario adaptability through automatic feature extraction and nonlinear mapping. …”
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Advancing County-Level Potato Cultivation Area Extraction: A Novel Approach Utilizing Multi-Source Remote Sensing Imagery and the Shapley Additive Explanations–Sequential Forward S... by Qiao Li, Xueliang Fu, Honghui Li, Hao Zhou

“…We employed the harmonic analysis of NDVI time–series (HANTS) method to extract features from the time–series and evaluated the classification accuracy across five feature sets: vegetation index time–series features, band means, vegetation index means, texture features, and color space features. …”
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DFN-YOLO: Detecting Narrowband Signals in Broadband Spectrum by Kun Jiang, Kexiao Peng, Yuan Feng, Xia Guo, Zuping Tang

“…Detecting narrowband signals under broadband environments, especially under low-signal-to-noise-ratio (SNR) conditions, poses significant challenges due to the complexity of time–frequency features and noise interference. To this end, this study presents a signal detection model named deformable feature-enhanced network–You Only Look Once (DFN-YOLO), specifically designed for blind signal detection in broadband scenarios. …”
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A Compact Shared-Aperture Antenna With 2-Transmit and 2-Receive Highly-Isolated Ports for Full-Duplex MIMO Systems by Junhui Rao, Zhaoyang Ming, Jichen Zhang, Zan Li, Chi-Yuk Chiu, Ross Murch

“…In this work, a compact multiple-input multiple-output (MIMO) IBFD antenna featuring two co-polarized transmit (Tx) ports and two co-polarized receive (Rx) ports is proposed that is suitable for use in mobile devices. …”
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Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems by Saud S. Alotaibi, Turki Ali Alghamdi

“…This study presents a League Championship Algorithm Feature Selection with Optimal Deep Learning based Cyberattack Detection (CLAFS-ODLCD) technique for securing the digital ecosystem. …”
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HY-Deepnet : A new Optimal Deep transfer learning empowered framework for an autonomous Alzheimer’s disease detection and diagnosis system by S. Veluchamy, R. Bhuvaneswari, K. Ashwini, Samah Alshathri, Walid El-Shafai

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An enhanced YOLOv8 model for accurate detection of solid floating waste by Juxing Di, Kaikai Xi, Yang Yang

“…This results in the development of an enhanced model that integrates feature enhancement, interference suppression, and localization optimization. …”
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Subsea Nodule Recognition and Deployment Detection Method Based on Improved YOLOv8s by Jixin Li, Junchao Li, Bin Su, Yuxin Cui

“…These modifications enhance feature extraction capabilities in the presence of uneven lighting and background interference, optimizing nodule segmentation in complex backgrounds and improving small-target detection performance. …”
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Improved classification algorithm for hyperspectral remote sensing images based on the hybrid spectral network model by Lv Deguo

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Remote sensing image protection using CTRSU-Net, SegNet + and ensemble learning by De Li, Chao Song, Xun Jin

“…To extract features with strong anti-interference ability, we propose a Convolutional block attention module-based Transformer Remote Sensing U-Net (CTRSU-Net) model and a SegNet + model. …”
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Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

“…This framework model consists of three parts: a backbone network, a multi-scale feature representation network, and a detection head. …”
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CGDU-DETR: An End-to-End Detection Model for Ship Detection in Day–Night Transition Environments by Wei Wu, Xiyu Fan, Zhuhua Hu, Yaochi Zhao

“…., strong reflections, low light), we designed a novel CG-Net model based on cascaded group attention and introduced a dynamic feature upsampling algorithm, effectively enhancing the model’s ability to extract multi-scale features and detect targets in complex backgrounds. …”
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LEM-Detector: An Efficient Detector for Photovoltaic Panel Defect Detection by Xinwen Zhou, Xiang Li, Wenfu Huang, Ran Wei

“…To handle defects of varying scales, complementary semantic information from different feature layers is leveraged for enhanced feature fusion. …”
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