Zobrazeno 1 - 10
of 3 765
pro vyhledávání: '"LI Lingling"'
Publikováno v:
Shuitu Baochi Xuebao, Vol 38, Iss 1, Pp 396-408 (2024)
[Objective] The Loess Plateau is a great geographical unit of China, which has important strategic significance for national food security and ecological security. Through long-term slope management, comprehensive watershed management, afforestation
Externí odkaz:
https://doaj.org/article/1704bbe0a3664752a866af7712eac7af
Autor:
Li Lingling
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
The integration of civic and political elements into the English classroom is an innovative way to give full play to the role of college education in cultivating students’ worldview, outlook on life, and values, while student participation is an ef
Externí odkaz:
https://doaj.org/article/7ff6fd1374b54450bef0339216fb1684
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Reasonable determination of the installation inclination and array spacing of PV power plant modules is essential to improve the power generation efficiency of PV power plants. This paper firstly derives the formula for calculating the north-south sp
Externí odkaz:
https://doaj.org/article/46f092497b6842419eeee25708564da6
Autor:
Li Lingling
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
To better cultivate talents in the direction of “Microbiological Pharmaceutical Technology”. In this paper, we first mine the Civic Elements from the Microbial Pharmaceuticals course with the help of a clustering algorithm and calculate the simil
Externí odkaz:
https://doaj.org/article/7f1ac97ea02147c1a192b99bdd138281
Publikováno v:
Zhongguo quanke yixue, Vol 26, Iss 11, Pp 1389-1397 (2023)
Background Previous studies have shown various improvement effects of non-invasive brain stimulation (NIBS) on autism spectrum disorder (ASD), and there is a lack of comparison of the efficacy of different types of NIBS. Objective To systematically e
Externí odkaz:
https://doaj.org/article/5cef1182c97c48869cbbbdc549af782b
Autor:
Ding, Henghui, Hong, Lingyi, Liu, Chang, Xu, Ning, Yang, Linjie, Fan, Yuchen, Miao, Deshui, Gu, Yameng, Li, Xin, He, Zhenyu, Wang, Yaowei, Yang, Ming-Hsuan, Chai, Jinming, Ma, Qin, Zhang, Junpei, Jiao, Licheng, Liu, Fang, Liu, Xinyu, Zhang, Jing, Zhang, Kexin, Liu, Xu, Li, LingLing, Fang, Hao, Pan, Feiyu, Lu, Xiankai, Zhang, Wei, Cong, Runmin, Tran, Tuyen, Cao, Bin, Zhang, Yisi, Wang, Hanyi, He, Xingjian, Liu, Jing
Despite the promising performance of current video segmentation models on existing benchmarks, these models still struggle with complex scenes. In this paper, we introduce the 6th Large-scale Video Object Segmentation (LSVOS) challenge in conjunction
Externí odkaz:
http://arxiv.org/abs/2409.05847
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-23, 2024, Art no. 5638023
Satellite imagery, due to its long-range imaging, brings with it a variety of scale-preferred tasks, such as the detection of tiny/small objects, making the precise localization and detection of small objects of interest a challenging task. In this a
Externí odkaz:
http://arxiv.org/abs/2409.05624
Video Object Segmentation (VOS) presents several challenges, including object occlusion and fragmentation, the dis-appearance and re-appearance of objects, and tracking specific objects within crowded scenes. In this work, we combine the strengths of
Externí odkaz:
http://arxiv.org/abs/2408.10469
Autor:
Gao, Zihan, Li, Lingling, Jiao, Licheng, Liu, Fang, Liu, Xu, Ma, Wenping, Guo, Yuwei, Yang, Shuyuan
Understanding 3D scenes is a crucial challenge in computer vision research with applications spanning multiple domains. Recent advancements in distilling 2D vision-language foundation models into neural fields, like NeRF and 3DGS, enables open-vocabu
Externí odkaz:
http://arxiv.org/abs/2407.01220
Autor:
Fu, Ying, Li, Yu, You, Shaodi, Shi, Boxin, Chen, Linwei, Zou, Yunhao, Wang, Zichun, Li, Yichen, Han, Yuze, Zhang, Yingkai, Wang, Jianan, Liu, Qinglin, Yu, Wei, Lv, Xiaoqian, Li, Jianing, Zhang, Shengping, Ji, Xiangyang, Chen, Yuanpei, Zhang, Yuhan, Peng, Weihang, Zhang, Liwen, Xu, Zhe, Gou, Dingyong, Li, Cong, Xu, Senyan, Zhang, Yunkang, Jiang, Siyuan, Lu, Xiaoqiang, Jiao, Licheng, Liu, Fang, Liu, Xu, Li, Lingling, Ma, Wenping, Yang, Shuyuan, Xie, Haiyang, Zhao, Jian, Huang, Shihua, Cheng, Peng, Shen, Xi, Wang, Zheng, An, Shuai, Zhu, Caizhi, Li, Xuelong, Zhang, Tao, Li, Liang, Liu, Yu, Yan, Chenggang, Zhang, Gengchen, Jiang, Linyan, Song, Bingyi, An, Zhuoyu, Lei, Haibo, Luo, Qing, Song, Jie, Liu, Yuan, Li, Qihang, Zhang, Haoyuan, Wang, Lingfeng, Chen, Wei, Luo, Aling, Li, Cheng, Cao, Jun, Chen, Shu, Dou, Zifei, Liu, Xinyu, Zhang, Jing, Zhang, Kexin, Yang, Yuting, Gou, Xuejian, Wang, Qinliang, Liu, Yang, Zhao, Shizhan, Zhang, Yanzhao, Yan, Libo, Guo, Yuwei, Li, Guoxin, Gao, Qiong, Che, Chenyue, Sun, Long, Chen, Xiang, Li, Hao, Pan, Jinshan, Xie, Chuanlong, Chen, Hongming, Li, Mingrui, Deng, Tianchen, Huang, Jingwei, Li, Yufeng, Wan, Fei, Xu, Bingxin, Cheng, Jian, Liu, Hongzhe, Xu, Cheng, Zou, Yuxiang, Pan, Weiguo, Dai, Songyin, Jia, Sen, Zhang, Junpei, Chen, Puhua
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to inform and enhance deep learning models, we can develop more robust and ac
Externí odkaz:
http://arxiv.org/abs/2406.10744