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  • 【每天一学】ECA(Efficient Channel Attention) - CSDN博客
    本文介绍了YOLOv13中高效 通道注意力机制(ECA) 的实现原理与代码实践。 ECA 通过自适应 一 维卷积核设计,在保持 注意力 效果的同时显著降低了计算复杂度。
  • 即插即用模块 ECA-Net: Efficient Channel Attention for Deep Convolutional . . .
    这种方式直接计算通道注意力系数,并且只有 k 个参数,大大减少了模型复杂度,同时利用卷积操作,信息在全局范围内得到传播;ECA的结构图如下
  • 深度学习模块4-ECA模块 - 简书
    ECA模块旨在通过引入一种高效的通道注意力机制来增强深度卷积神经网络的特征表示能力。 它着重于捕获通道间的动态依赖关系,从而使网络能够更加精确地重视对当前任务更重要的特征,提升模型在各种视觉任务上的性能。
  • Early College Academy - LA Trade Tech College
    ECA is a California Distinguished School Recipient! For the first time, ECA has been awarded the prestigious California Distinguished School Award! It is a recognition of all the hard work of our students, parents, partners and staff
  • ECA-Net: Efficient Channel Attention for Deep Convolutional Neural . . .
    Recently, channel attention mechanism has demonstrated to offer great potential in improving the performance of deep convolutional neural networks (CNNs) However, most existing methods dedicate to developing more sophisticated attention modules for achieving better performance, which inevitably increase model complexity To overcome the paradox of performance and complexity trade-off, this
  • ECA-Net:深度卷积神经网络中的高效通道注意力机制【原理讲解及代码!!!】_eca模块-CSDN博客
    本文详细介绍了ECA-Net,一种在深度学习特别是DCNN中通过高效和自适应的通道注意力机制提升模型性能的技术。 ECA模块通过一维卷积捕捉通道依赖,具有计算高效、信息完整保留和自适应核大小等优势,适用于各种CNN结构的优化。
  • ECA-Net: Efficient Channel Attention - GitHub
    To overcome the paradox of performance and complexity trade-off, this paper proposes an EfficientChannel Attention (ECA) module, which only involves a handful of parameters while bringing clear performance gain
  • ECA-Net介绍 - 知乎
    ECA-Net(Efficient Channel Attention Network)是一种用于计算机视觉任务的注意力模型,旨在增强神经网络对图像特征的建模能力。




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