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pro vyhledávání: '"LI, GUANGLIN"'
Autor:
Ni, Junjie, Zhang, Guofeng, Li, Guanglin, Li, Yijin, Liu, Xinyang, Huang, Zhaoyang, Bao, Hujun
We tackle the efficiency problem of learning local feature matching. Recent advancements have given rise to purely CNN-based and transformer-based approaches, each augmented with deep learning techniques. While CNN-based methods often excel in matchi
Externí odkaz:
http://arxiv.org/abs/2410.22733
Autor:
Shen, Yichen, Li, Yijin, Chen, Shuo, Li, Guanglin, Huang, Zhaoyang, Bao, Hujun, Cui, Zhaopeng, Zhang, Guofeng
Feature tracking is crucial for, structure from motion (SFM), simultaneous localization and mapping (SLAM), object tracking and various computer vision tasks. Event cameras, known for their high temporal resolution and ability to capture asynchronous
Externí odkaz:
http://arxiv.org/abs/2409.17981
In recent years, the paradigm of neural implicit representations has gained substantial attention in the field of Simultaneous Localization and Mapping (SLAM). However, a notable gap exists in the existing approaches when it comes to scene understand
Externí odkaz:
http://arxiv.org/abs/2407.20853
Autor:
Hu, Jiarui, Chen, Xianhao, Feng, Boyin, Li, Guanglin, Yang, Liangjing, Bao, Hujun, Zhang, Guofeng, Cui, Zhaopeng
Recently neural radiance fields (NeRF) have been widely exploited as 3D representations for dense simultaneous localization and mapping (SLAM). Despite their notable successes in surface modeling and novel view synthesis, existing NeRF-based methods
Externí odkaz:
http://arxiv.org/abs/2403.16095
Autor:
Samuel, Oluwarotimi Williams, Asogbon, Mojisola Grace, Khushaba, Rami, Kulwa, Frank, Li, Guanglin
Publikováno v:
IEEE Transactions on Biomedical Engineering, November 2022
Surface electromyogram (sEMG) is arguably the most sought-after physiological signal with a broad spectrum of biomedical applications, especially in miniaturized rehabilitation robots such as multifunctional prostheses. The widespread use of sEMG to
Externí odkaz:
http://arxiv.org/abs/2211.07378
Autor:
Li, Guanglin, Li, Yifeng, Ye, Zhichao, Zhang, Qihang, Kong, Tao, Cui, Zhaopeng, Zhang, Guofeng
Empowering autonomous agents with 3D understanding for daily objects is a grand challenge in robotics applications. When exploring in an unknown environment, existing methods for object pose estimation are still not satisfactory due to the diversity
Externí odkaz:
http://arxiv.org/abs/2210.01112
Autor:
Kulwa, Frank, Samuel, Oluwarotimi Williams, Asogbon, Mojisola Grace, Obe, Olumide Olayinka, Li, Guanglin
The use of deep neural networks in electromyogram (EMG) based prostheses control provides a promising alternative to the hand-crafted features by automatically learning muscle activation patterns from the EMG signals. Meanwhile, the use of raw EMG si
Externí odkaz:
http://arxiv.org/abs/2209.05804
Autor:
Zhou, Ye, Qamar, Obaid Ali, Byoung Hwang, Gi, Knapp, Caroline, Li, Guanglin, Lubineau, Gilles, Tai, Yanlong
Publikováno v:
In Chemical Engineering Journal 15 November 2024 500
Publikováno v:
In International Journal of Biological Macromolecules November 2024 281 Part 2
Autor:
He, Panyu, Fu, Xinglan, Wang, Chenghao, Gou, Yujiang, Cao, Fengjing, Tian, Hongwu, Ma, Shixiang, Liang, Yiyi, An, Ting, Li, Guanglin
Publikováno v:
In Sensors and Actuators: B. Chemical 15 January 2025 423