Feature Fusion Attention Network(FFANet)是一种用于单图像去雾(Single Image Dehazing)的深度学习方法。以下是对FFANet的详细解答: 1. FFANet的基本原理 FFANet是一种端到端的特征融合注意力网络,旨在直接恢复无雾图像。它通过结合特征融合和注意力机制,有效处理图像中的雾霾问题。FFANet的核心思想在于,通过特征注意...
FFA - Net架构由三个关键组件组成: 1).一种新颖的特征注意力(Feature Attention,FA)模块将通道注意力(Channel Attention)和像素注意力(Pixel Attention)机制相结合,考虑到不同通道特征包含的权重信息完全不同,雾霾在不同图像像素上分布不均匀。FA特殊地对待不同的特征和像素,为处理不同类型的信息提供了额外的灵活性...
论文原文+开源代码需要的同学关注“学姐带你玩AI”公号(不懂的看我主页签名),那边回复“AFF新”获取。 Attention-based acoustic feature fusion network for depression detection 方法:论文提出了一种基于注意力机制的声学特征融合网络,用于检测抑郁症。ABAFnet结合了四种不同的声学特征到一个综合的深度学习模型中,有...
Section 3 introduces the proposed efficient attention feature fusion network in detail. Section 4 analyzes the quantitative and qualitative experimental results. In Section 5, we conclude this research. Access through your organization Check access to the full text by signing in through your ...
FFA-Net: Feature Fusion Attention Network for Single Image Dehazing(AAAI 2020) Official implementation. by Xu Qin, Zhilin Wang et al. Peking University and Beijing University of Aeronautics & Astronautics. Citation To be determined. Dependencies and Installation ...
Attention-based acoustic feature fusion network for depression detection 方法:论文提出了一种基于注意力机制的声学特征融合网络,用于检测抑郁症。ABAFnet结合了四种不同的声学特征到一个综合的深度学习模型中,有效地整合和融合了多层次的特征。作者还提出了一种新颖的权重调整模块,用于后期融合,通过有效地综合这些特征...
A new efficient pedestrian detection network with infrared and visible dual-modality is proposed.A feature attention fusion module is proposed, which reduces redundant information and improves the fusion effect of features.A deep attention pyramid module that can enhance the features of small pedestrian...
In this paper, we propose an end-to-end feature fusion at-tention network (FFA-Net) to directly restore the haze-free image. The FFA-Net architecture consists of three key components: 1) A novel Feature Attention (FA) module combines Channel Attention with Pixel Attention mechanism, considerin...
An efcient lightweight network for image denoising using progressive residual and convolutional attention feature fusion 方法:作者提出了一种新颖的网络架构,这种架构融合了轻量级残差和注意力机制,目的是解决现有图像去噪方法中由于网络深度过大而导致的计算负担问题。
In this paper, we start from these two aspects, and we propose a self-attention feature fusion network for semantic segmentation (SA-FFNet) to improve semantic segmentation performance. Specifically, we introduced the vertical and horizontal compression attention module (VH-CAM) and the unequal ...