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    Colony Binary Classification Based on Persistent Homology Feature Extraction and Improved EfficientNet by Zumin Wang, Ke Yang, Jie Tang, Jun Gao, Yuhao Zhang, Wei Xu, Chun-Ming Huang

    Published 2025-06-01
    “…To achieve accurate and efficient colony classification, this paper proposes a high-precision method based on Persistent Homology (PH) and an improved EfficientNet. Specifically, (1) a PH feature extraction algorithm is applied to Candida albicans (CA) and Staphylococcus epidermidis (SE) colonies cultured for 18 h in Petri dishes to capture their topological information. (2) The Mobile Inverted Bottleneck Convolution (MBConv) module in EfficientNet is modified, enhancing the attention mechanism to better handle local small targets. (3) A novel self-attention mechanism named the Spatial and Contextual Transformer (SCoT), which is introduced to process information at multiple scales, increasing the resolution in orthogonal directions of the image and the aggregation capability of feature maps. …”
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    A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet by Muhammad Waqas Ahmed, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz Alhammadi, Asaad Algarni, Ahmad Jalal, Jeongho Cho

    Published 2025-01-01
    “…Leveraging the power of deep learning, a DenseNet architecture achieves superior classification accuracy based on the optimized feature set. …”
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    A Solution Method for Partial Differential Equations by Fusing Fourier Operators and U-Net by Tao Zhang, Xinran Zhu

    Published 2025-03-01
    “…This paper presents an innovative method based on the combination of a U-Net neural network with Fourier neural operators, aiming to improve the accuracy and efficiency of solving partial differential equations. …”
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    Yaw Noise Fault Detection for Wind Turbines Based on ResNet-Transformer Model by CHEN Yanan, HU Kaikai, LI Ziyuan, WANG Lipeng

    Published 2025-02-01
    “…To enhance the accuracy of diagnosing yaw noise faults in wind turbines, this paper develops a deep residual network (ResNet)-Transformer model based on acoustic signals. …”
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    CSA-Net: Complex Scenarios Adaptive Network for Building Extraction for Remote Sensing Images by Dongjie Yang, Xianjun Gao, Yuanwei Yang, Minghan Jiang, Kangliang Guo, Bo Liu, Shaohua Li, Shengyan Yu

    Published 2024-01-01
    “…Therefore, we propose a complex scenarios adaptive network (CSA-Net) for building extraction. CSA-Net is comprised of the hierarchical-context feature extraction (HFE) module, the global-local feature interaction (GFI) module, and the multiscale-adaptive feature fusion (MFF) structure. …”
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    Radio Frequency Interference Detection Using Swin Transformer Embedding U2-Net by Shengdi Chen, Bo Liang

    Published 2025-01-01
    “…To this end, we propose a novel deep learning–based RFI detection model named ST-U2Net, which combines the Swin Transformer and the Residual U-block (RSU) of U2-Net to form a dual-encoder architecture. …”
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    EPIMR: Prediction of Enhancer-Promoter Interactions by Multi-Scale ResNet on Image Representation by Qiaozhen Meng, Yinuo Lyu, Xiaoqing Peng, Junhai Xu, Jijun Tang, Fei Guo

    Published 2024-09-01
    “…First, Hilbert Curve is utilized to represent sequences to images to preserve the position and spatial information. Second, a multi-scale residual neural network (ResNet) is used to learn the distinguishing features of different abstraction levels. …”
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