The fTAN includes three modules: feature extraction module, Multi-scale Dilated Deformable (MDD) alignment module and attention module. 特征提取模块、多尺度扩张变形(MDD)对齐模块和注意力模块。 1)Feature Extraction Module: 特征提取模块: 由一个卷积层和 5 个带有 ReLU 激活函数的残差块[38] 组成。 使...
Compressed multi-scale feature fusion network for single image super-resolutionDeep neural networkMulti-scale feature fusionNetwork compressionStructured sparsitySuper-resolution
In this paper, for hyperspectral single-image super-resolution, we propose a multi-scale feature fusion and aggregation network with 3D convolution (MFFA-3D) by cascading the MFFA-3D block. The MFFA-3D block includes group multi-scale feature fusion part and multi-scale feature aggregation part....
以下是multi-scale feature fusion的计算公式: F =Σ(Wi * Gi) 其中,F表示融合后的特征向量,Wi表示第i个尺度上特征向量的权重系数,Gi表示第i个尺度上提取的特征向量。权重系数可以根据具体情况进行调整,通常采用softmax函数进行归一化处理,以保证各尺度特征向量的权重之和为1。 在计算过程中,首先从不同尺度的...
论文阅读《Self-Attention Guidance and Multiscale Feature Fusion-Based UAV Image Object Detection》 Tywwhale 1 人赞同了该文章 摘要 无人机(UAV)图像的目标检测是近年来研究的热点。现有的目标检测方法在一般场景上取得了很好的结果,但无人机图像存在固有的挑战。无人机图像的检测精度受到复杂背景、显著尺度差异...
In this paper, a multi-scale feature fusion module is introduced into the graph convolutional network model, and the high-resolution low-level feature information in the feature map is fused with the semantic information of the high-level feature, which greatly improves the model's recognition ...
scale feature maps, respectively. Then, the two feature maps with the same scale in both groups are sent together to the corresponding LFFM module for feature fusion. The fused multi-scale feature maps are fed into the MSFA module, which directly aggregates the multi-scale feature maps and ...
Enhancing Medical Image Segmentation with TransCeption: A Multi-Scale Feature Fusion Approach 阿梁 3 人赞同了该文章 论文动机 (1)尽管hierarchical encoder中的transformer块在不同的阶段捕捉全局信息,但transformer块只处理patch merging后的特征层,该特征层使用单一的感受野的大小。因此,在每个阶段中没有适当地利用...
Multi-Scale Boosted Dehazing Network with Dense Feature Fusion笔记和代码 本篇论文的主要创新点是SOS增强策略和密集特征融合,创新点均是从其他领域进行挖掘。 摘要 提出了一种基于U-Net结构的具有密集特征融合的多尺度增强去雾网络。 该方法基于增强反馈和误差反馈两种原理进行了设计,并证明了该方法适用于脱雾问题。
A superresolution imaging approach that localizes very small targets, such as red blood cells or droplets of injected photoacoustic dye, has significantly improved spatial resolution in various biological and medical imaging modalities. However, this superior spatial resolution is achieved by sacrificing ...