总体而言,工作的主要贡献总结如下: •提出了一种称为双结构特征网络(DSF-Net)的有效方法,通过结合欧几里得结构数据和非欧几里得结构数据的特征来解决人员重识别的遮挡问题。DSF-Net每个分支都设计了专门用于遮挡问题的相关算法。为了基于欧几里得结构提取更好的特征,设计了一个基于位置注意机制的 dropout 块,称为位置注...
本文利用静态和动态信息融合的方式提出一个在卫星视频中检测运动目标的双流检测网络(DSFNet)。具体来说,DSFNet由2部分组成,一是2D骨干网络提取静态信息(帧内的上下文信息),二是轻量的3D骨干网络提取动态的连续帧间的运动信息。之后把提取的动态和静态信息融合,送到检测头当中去检测卫星视频的移动目标。数据集是使用...
To address these challenges, we propose the DSF-Net, a novel framework specifically designed to enhance small SAR ship detection performance. Within this framework, we introduce the Pixel-wise Shuffle Attention module (PWSA) as a pivotal step to strengthen the feature extraction capabilit...
To address these challenges, we propose the DSF-Net, a novel framework specifically designed to enhance small SAR ship detection performance. Within this framework, we introduce the Pixel-wise Shuffle Attention module (PWSA) as a pivotal step to strengthen the feature extraction capability. To ...
DSFNet Paper link:https://arxiv.org/abs/2305.11522 Project link:https://lhyfst.github.io/dsfnet/ Requirements python 3.6.13 pytorch 1.7.1 cudatoolkit 10.1.243 imageio 2.15.0 numpy 1.19.2 opencv-python 4.7.0.72 PyYAML 6.0 scikit-image 0.17.2 torchvision 0.8.2 tqdm 4.64.1 trimesh 3.22....
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Code for Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images - apprisi/DSFANet
We propose the DSF-Net to tackle the challenges of small target feature loss, background-target confusion, dense ship detection overlap, and network structure stability. The DSF-Net comprises two kinds of shuffle-guided attention mechanisms, from fine to coarse. It also includes a multi-scale fe...
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A delegate is a powerful tool that allows the managed code object model designer to encapsulate method calls. Delegates are useful for event notifications and callback functions. Event notifications Use the appropriate event design pattern for events even if the event is not user interface-related....