Zhenkun Lu

Enhanced sparrow search algorithm with DV-Hop for high-precision fire sensor localization in underground spaces

Li Jiang, Liliang Dong, Le Xu, Fangqiong Luo et autres

Fire monitoring in underground spaces is critical for emergency response, yet traditional localization methods like DV-Hop suffer from significant localization errors due to hop count ambiguity and premature convergence in optimization. To address these issues, we propose an Enhanced Sparrow Search Algorithm …

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Multimodal and multiscale learning network for efficient polyp segmentation

Yuyang Jie, Wei Wang, Wentao Shi, Zhenkun Lu

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Polyp Image Segmentation Algorithm Based on Improved Polyp-PVT

Zhenkun Lu

Polyp detection is crucial for preventing colorectal cancer. Polyp segmentation based on deep learning enables pixellevel lesion analysis, with significant clinical value. This paper proposes PVT-SMC, an improved model based on Polyp-PVT, integrating SE_MHA (fusing SE and MHA) and CBAM to enhance …

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Joint Segmentation of Optic Disc and Cup Using Attention Mechanism and Context Aggregation

Zhiyong Zeng, Zhenkun Lu, Shuang Han, Lang Chen

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Biclustering-KNN joint learning in anomaly detection for handling class-imbalance-problem

Zhenkun Lu, Haohan Wei, Fengyu Ye, Qinghua Huang

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Multi-scale temporal representation with sparse dynamic graph learning for district heat load forecasting

Yaohui Huang, Peisong Zhang, Zhenkun Lu, Zhikai Ni

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Rib Fracture Segmentation Based on 3D CE-Unet

Shuang Han, Zhenkun Lu, Lang Chen, Peng Yu

Due to the structural complexity of the rib cage and the diversity of fracture forms, traditional image segmentation methods often struggle to cope, resulting in unsatisfactory performance in terms of accuracy and robustness. These limitations not only affect the accurate diagnosis of …

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Time optimal trajectory planning of robotic arm based on improved sand cat swarm optimization algorithm

Zhenkun Lu, Zhichao You, B. Xia

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LM-Net: A Light-weight and Multi-scale Network for Medical Image Segmentation

Zhenkun Lu, Wei Wang, Qinghua Huang

Current medical image segmentation approaches have limitations in deeply exploring multi-scale information and effectively combining local detail textures with global contextual semantic information. This results in over-segmentation, under-segmentation, and blurred segmentation boundaries. To tackle these challenges, we explore multi-scale feature representations from …

Fault Detection and Estimation for Drag-Free Satellite Actuator Based on Adaptive Sliding Mode Observer

Jikun Yang, Zhenkun Lu, Zhanxiu Wang, Lei Wang et autres

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Research on Medical Image Fusion Based on Multi-Scale Dual-Branch Pyramid Attention Network

Xibin Zhang, Zhenkun Lu

Medical image fusion technology integrates complementary information from multimodal medical images. This technology plays a significant role in clinical applications. The article introduces a novel convolutional neural network, termed the Multi-Scale Dual-Branch Pyramid Attention (MSPA) network, for fusing multimodal medical images. The …

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Ultra-compact narrow-band band-stop filter based on inverse design

Xiaopeng Huang, Jiaao Li, Zhicheng Wang, Haitang Li et autres

Traditional on-chip filters are usually devoid of algorithmic utilization and span several hundred micrometers or greater in length, thereby constraining the compactness of the device. This study presents a design of an ultra-compact narrow-band band-stop filter with a high extinction ratio and …

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