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1,391 results on '"Xiong, Juan"'

2. Cross-CBAM: A Lightweight network for Scene Segmentation

Author

Zhang, Zhengbin, Xu, Zhenhao, Gu, Xingsheng, and Xiong, Juan

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Scene parsing is a great challenge for real-time semantic segmentation. Although traditional semantic segmentation networks have made remarkable leap-forwards in semantic accuracy, the performance of inference speed is unsatisfactory. Meanwhile, this progress is achieved with fairly large networks and powerful computational resources. However, it is difficult to run extremely large models on edge computing devices with limited computing power, which poses a huge challenge to the real-time semantic segmentation tasks. In this paper, we present the Cross-CBAM network, a novel lightweight network for real-time semantic segmentation. Specifically, a Squeeze-and-Excitation Atrous Spatial Pyramid Pooling Module(SE-ASPP) is proposed to get variable field-of-view and multiscale information. And we propose a Cross Convolutional Block Attention Module(CCBAM), in which a cross-multiply operation is employed in the CCBAM module to make high-level semantic information guide low-level detail information. Different from previous work, these works use attention to focus on the desired information in the backbone. CCBAM uses cross-attention for feature fusion in the FPN structure. Extensive experiments on the Cityscapes dataset and Camvid dataset demonstrate the effectiveness of the proposed Cross-CBAM model by achieving a promising trade-off between segmentation accuracy and inference speed. On the Cityscapes test set, we achieve 73.4% mIoU with a speed of 240.9FPS and 77.2% mIoU with a speed of 88.6FPS on NVIDIA GTX 1080Ti.

Published
2023

6. Outline of Jie Lu's Education Thoughts

Author

Xiong, Juan, Liu, Mingyuan, Cao, Shu, and Cao, Huiying

Abstract

As a famous contemporary educator and educational theorist in China, Jie Lu has always been concerned about people and their lives and moral conditions since the 1970s and 1980s. With this as the center, a systematic "human understanding" pedagogy and moral education were constructed. His thoughts reflect the times' distinctive characteristics, and scholars have widely praised his noble research quality and scholarly ideological state. Given this, this paper reviews Jie Lu's moral education thoughts based on the research on Jie Lu's education thoughts and feelings to make a more comprehensive and systematic review of Jie Lu's moral education thoughts.

Published
2021

20. Comprehensive Evaluation of Xiaoman Zhu's Emotional Education Theory

Author

Xiong, Juan

Abstract

Professor Xiaoman Zhu is the theoretical initiator and the promoter of contemporary emotional education in China. Since the 1980s and 1990s, she has led the research on China's emotional education and has put forward many pioneering insights, forming a rich and systematic emotional education theory. She has been involved in guiding several experimental schools and research bases for a long time committed to the proper combination of emotional education theory and school education. She infiltrated it into moral education, teacher education, textbooks, courses, etc., and her theory has been widely recognized. This paper evaluates the source, theoretical basis, and practice of Xiaoman Zhu's emotional education as a whole, intending to construct a theoretical cognitive framework to describe Xiaoman Zhu's educational thought and theory in a more comprehensive manner.

Published
2020

42. Integrated analysis of the microbiome and transcriptome in stomach adenocarcinoma

Author

Zhou Daxiang, Xiong Shu, Xiong Juan, Deng Xuesong, Long Quanzhou, and Li Yanjie

Subjects
stomach adenocarcinoma, microbiota, subtype, prognostic model, immune infiltration, Biology (General), QH301-705.5
Abstract

We aimed to characterize the stomach adenocarcinoma (STAD) microbiota and its clinical value using an integrated analysis of the microbiome and transcriptome. Microbiome and transcriptome data were downloaded from the Cancer Microbiome Atlas and the Cancer Genome Atlas databases. We identified nine differentially abundant microbial genera, including Helicobacter, Mycobacterium, and Streptococcus, which clustered patients into three subtypes with different survival rates. In total, 74 prognostic genes were screened from 925 feature genes of the subtypes, among which five genes were identified for prognostic model construction, including NTN5, MPV17L, MPLKIP, SIGLEC5, and SPAG16. The prognostic model could stratify patients into different risk groups. The high-risk group was associated with poor overall survival. A nomogram established using the prognostic risk score could accurately predict the 1, 3, and 5 year overall survival probabilities. The high-risk group had a higher proportion of histological grade 3 and recurrence samples. Immune infiltration analysis showed that samples in the high-risk group had a higher abundance of infiltrating neutrophils. The Notch signaling pathway activity showed a significant difference between the high- and low-risk groups. In conclusion, a prognostic model based on five feature genes of microbial subtypes could predict the overall survival for patients with STAD.

Published
2023
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