期刊名称: Information Fusion 论文地址: 10.1109/MVIPIT60427.2023.00035 作者: 单位: 北京大学计算机学院 1.研究目的 该论文的主要研究目的是开发一种基于变压器的多模态跨尺度特征融合网络,用于提高复杂环境下车辆检测的准确性和鲁棒性。为了应对在不同环境(如白天与夜晚、晴天与雾天)下的车辆检测挑战,作者引入了多...
In this paper, we propose an cross-scale feature fusion network (CFFNet) to harvest the compact segmentatiHon model with high accuracy. Specifically, we design a novel lightweight residual block in backbone with increasing block depth strategy instead of inverted residual block with increasing ...
CSFFNet: Lightweight cross鈥恠cale feature fusion network for salient object detection in remote sensing imagesSalient object detection (SOD), one of the ... L Wang,C Long,X Li,... 被引量: 0发表: 2023...
CF2PN: A Cross-Scale Feature Fusion Pyramid Network Based Remote Sensing Target Detection 来自 Semantic Scholar 喜欢 0 阅读量: 277 作者:W Huang,G Li,Q Chen,M Ju,J Qu 摘要: In the wake of developments in remote sensing, the application of target detection of remote sensing is of ...
Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence ...
Multi-Scale Feature Fusion 为了让两个分支的数据可以进行融合交互,提出了多种方案 All-Attention: 直接两个分支拿过来一起计算注意力【计算开销大】 Class Token Fusion:只是用 Class Token 进行混合(直接使用加法) Pairwise Fusion:基于 patch 所属的空间位置进行混合——这里会先进行插值来对其空间大小,然后再进行...
设计了一种新的多粒度共享特征融合(Multiple-granularity Shared Feature Fusion, MSFF)网络,所提MSFF框架旨在学习两种模态共享的全局和局部特征表示,是一种多分支网络体系结构。在框架中,采用一个全局特征表示的分支和两个用于局部特征表示的分支组成。本文将只有一个完整的全局信息看作最粗糙的信息,随着分块的增加,...
The recent Californian hot drought (2012–2016) precipitated unprecedented ponderosa pine (Pinus ponderosa) mortality, largely attributable to the western pine beetle (Dendroctonus brevicomis; WPB). Broad-scale climate conditions can directly shape tree
Multi-Scale Feature Fusion 有效的特征融合是学习多尺度特征表示的关键。作者探索了四种不同的方法融合解决策略:三种简单的启发式方法和所提出的交叉注意模块,如图3所示。 (a)全注意融合,将两个branch的token concatenate起来,而不考虑任何token的特征。 (b)类标token融合,class token可以视为是一个branch的全局特征...
By combining the new CS-NL prior with local and in-scale non-local priors in a powerful recurrent fusion cell, we can find more cross-scale feature correlations within a single low-resolution (LR) image. The performance of SISR is significantly improved by exhaustively integrating all possible...