每日一词 | 特征级融合 Feature Level Image Fusion 原标题：《每日一词 | 特征级融合 Feature Level Image Fusion》
Five different image sets were used to evaluate the proposed fusion algorithm. To compare the performance of this algorithm, three different pixel-level image fusion algorithms, viz. DWT, SWT, and DT-CWT, were also implemented and evaluated. From this study, it is concluded that FLIF provides ...
1. 特征抽取层融合 3.1 特征抽取层融合的语种辨识模型 特征抽取层融合(Feature-level Fusion)就是在如图2 所 示的特征矢量部分对多种不同特征 …www.docin.com|基于1 个网页 例句 释义: 全部,特征抽取层融合 更多例句筛选 1. Image fusion can be divided into three levels, pixel level fusion, feature lev...
In this paper, impact of feature level fusion and feature selection on multiple distorted image quality assessment is presented. To this end features are extracted from multiple distorted images using six NR-IQA techniques (BLIINDS-II, BRISQUE, CurveletQA, DIIVINE, GM-LOG, SSEQ) that extract ...
Feature level fusion is also implemented for other fields such as medical image fusion (Kor & Tiwary, 2004; Patnaik, 2006) object classification (Wender & Dietmayer, 2007), machinery fault diagnosis (Liu, Ma, & Mathew, 2006) and content-based image retrieval (Rahman, Desai, & Bhattacharya,...
Multi-Cue Visual Tracking Using Robust Feature-Level Fusion Based on Joint Sparse RepresentationL. Chen L Chen 被引量: 0发表: 2014年 Multi-cue Visual Tracking Based on Sparse Representation Under dynamic and complex environment, the single feature methods usually can't distinguish the target from ...
divide-and-conquer:根据object的scale在不同level上检测object common belief belief:FPN的成功依赖于多个level的feature的fusion 发展:产生了一系列复杂的fusion method(design manually / via NAS) 缺点:这些方法忽略了FPN中的divide-and-conquer 后果:很少有关于multi-scale feature fusion和divide-and-conquer对FPN贡...
Global and Local Multi-scale Feature Fusion Enhancement for Brain Tumor Segmentation and Pancreas Segmentation The fully convolutional networks (FCNs) have been widely applied in numerous medical image segmentation tasks. However, tissue regions usually have large variations of shape and scale, so the ...
CNN-combined graph residual network with multilevel feature fusion for hyperspectral image classification The application of graph convolutional networks (GCN) in hyperspectral image (HSI) classification has become a promising method, thanks to its flexible con... W Guo,G Xu,W Liu,... - 《Iet ...
摘要: Multimedia Systems - Fine-grained image retrieval (FGIR) has received extensive attention in academia and industry. Despite the tremendous progress, the issue of large intra-class differences and...关键词: Convolutional neural network Multi-level feature fusion Fine-grained image retrieval ...