In this paper, we propose a Multi-Semantic Aligned Graph Convolutional Network (MSAGCN), which contains two fundamental operations: multi-angle aggregation and semantic alignment, to resolve two challenges simultaneously. The core of MSAGCN is the aggregation of nodes that belong to the same class...
Handwriting verification - Comparison of a multi-algorithmic and a multi-semantic approach In this paper, a comparison of an existing multi-algorithmic and a new multi-semantic fusion approach for biometric online handwriting user verification is presented. First, in order to improve the authentication...
Therefore,finding the multi-relationships between the entities of a document is one of the key technologies for accurate topic identification in massive scientific or technological literatures.This paper firstly reviewed the research status of multi-relations fusion in topic identification,summarized the ...
Multi-modal Semantic Understanding with Contrastive Cross-modal Feature Alignment 主要内容 这篇文章的主要内容是关于多模态语义理解的研究,特别是通过对比学习进行跨模态特征对齐的方法。文章提出了一种新的CLIP(Contrastive Language-Image Pre-training)引导的对比学习方法,用于多模态特征对齐(CLFA,CLIP-guided Contrast...
视觉的识别与分割会更加容易。这就可以根据语义信息提高对环境的理解。文章《Multi-modal Semantic SLAM for Complex Dynamic Environments》提出了一个鲁棒的多模态语义框架去解决slam在复杂和动态环境下的问题。同时该论文也在Github中开源了数据集和代码。
论文阅读《Multi-modal Semantic SLAM for Complex Dynamic Environments》(arxiv, FLOAM作者的新作) 晃晃悠悠的虚无周 深入了解摸鱼技术7 人赞同了该文章 主要做的是语义信息融合辅助slam的工作,代码已开源:GitHub - wh200720041/MMS_SLAM,但是感觉这版的论文缺少了很多细节,尤其是实验部分,感觉很突兀,估计作者没放...
A cornerstone for mobile robots operating in man-made environments and interacting with humans is representing and understanding the human semantic concepts of space. In this paper, we present a multi-layered semantic mapping algorithm able to combine information about the existence of objects in the...
This paper is an attempt to bring out the multi level semantic structure in the light of functional theory by analyzing a short text, a short story and a novel. The findings in the analyses show how the first two levels of meaning are determined by the physical context, and how the deep...
First, we introduce a deep learning based algorithm for multi-class semantic segmentation addressing fourteen different tissue types in whole-slide images of colorectal cancer, including not only the primary cancer-associated epithelial and stroma classes but also some other more peripheral tissue types....
来自 Semantic Scholar 喜欢 0 阅读量: 143 作者: C Du 摘要: Multi-task learning has proven to be useful to boost the learning of multiple related but different tasks. Meanwhile, latent semantic models such as LSA and LDA are popular and effective methods to extract discriminative semantic ...