3. 解释说明 efficient multi-scale attention module 的关键要点: 3.1 多尺度特征提取和整合策略: 多尺度特征提取是指在图像或视频处理中,通过使用不同感受野大小的卷积核进行多层级的特征提取。在efficient multi-scale attention module中,采用了一种创新的策略来同时提取不同尺度下的特征。具体而言,模块中包含多个并...
Learning Spatial Fusion for Single-Shot Object Detection (1)目的:不同特征尺度之间的不一致性是基于特征金字塔的单阶段检测的主要缺陷。 (2)改进点:提出了新的金字塔特征融合策略,称为自适应空间特征融合(ASFF),通过学习权重参数的方式将不同层的特征融合到一起。 (3)网络结构 论文中的做法是自适应学习不同尺...
select article Multimodule imaging of the hierarchical equine hoof wall porosity and structure Research articleOpen access Multimodule imaging of the hierarchical equine hoof wall porosity and structure Mahmoud A. Mahrous, Charul Chadha, Pei L. Robins, Christian Bonney, ... Iwona Jasiuk ...
We propose OmniPose, a single-pass, end-to-end trainable framework, that achieves state-of-the-art results for multi-person pose estimation. Using a novel waterfall module, the OmniPose architecture leverages multi-scale feature representations that increase the effectiveness of backbone feature extra...
class MEEM(nn.Module): definit(self, in_dim, hidden_dim, width=4, norm=nn.BatchNorm2d, act=nn.GELU): super().init() self.in_dim = in_dim self.hidden_dim = hidden_dim self.width = width self.in_conv = nn.Sequential(
In this paper, we aim to improve the performance of single-image super-resolution (SISR) by designing a more effective feature extraction module and a bett
最后两个池化层和striding layer(作者把pooling和striding两个单词是一起用,其实也就是删去了最后两个stride=2的池化层)被完全去除,并插入上下文模块(就是在front-end后面加上context module)。另外,中间特征图的填充也被去除,作者仅将输入特征图填充了 33 的宽度。 整体的网络结构如下,一开始我还挺疑惑的,作者从...
Radial spokes (RS) transmit mechanochemical signals between the central pair (CP) and axonemal dynein arms to coordinate ciliary motility. Atomic-resolution structures of metazoan RS and structures of axonemal complexes in ependymal cilia, whose rhythmic
First, a novel multi-scale module is ingenious established based on dilated convolution, which is used as the key part to obtain differential features through different perceptual fields. Then, in order to further reduce the complexity of the proposed model, a global average pooling technology is ...
We propose the upgraded “Waterfall Atrous Spatial Pyramid” module, shown in Figure 2. WASPv2 is a novel architecture with Atrous Convolutions that is able to leverage both the larger Field-of-View of the Atrous Spatial Pyramid Pooling configuration and the reduced size of the cascade approach...