Zobrazeno 1 - 10
of 232
pro vyhledávání: '"Gao Jialin"'
Autor:
Guo, Xiuyuan, Xu, Chengqi, Guo, Guinan, Zhu, Feiyu, Cai, Changpeng, Wang, Peizhe, Wei, Xiaoming, Su, Junhao, Gao, Jialin
Currently, training large-scale deep learning models is typically achieved through parallel training across multiple GPUs. However, due to the inherent communication overhead and synchronization delays in traditional model parallelism methods, seamle
Externí odkaz:
http://arxiv.org/abs/2411.12780
Autor:
He, Runze, Ma, Kai, Huang, Linjiang, Huang, Shaofei, Gao, Jialin, Wei, Xiaoming, Dai, Jiao, Han, Jizhong, Liu, Si
Introducing user-specified visual concepts in image editing is highly practical as these concepts convey the user's intent more precisely than text-based descriptions. We propose FreeEdit, a novel approach for achieving such reference-based image edi
Externí odkaz:
http://arxiv.org/abs/2409.18071
Autor:
Gao, Jialin, Ong, Bill, Lwi, Darld, Ng, Zhen Hao, Yee, Xun Wei, Mak, Mun-Thye, Ng, Wee Siong, Ng, See-Kiong, Teo, Hui Ying, Khoo, Victor, Bökman, Georg, Edstedt, Johan, Brodt, Kirill, Boittiaux, Clémentin, Ferrera, Maxime, Konev, Stepan
Publikováno v:
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence Demo Track (2024) 8661-8664
Research in 3D mapping is crucial for smart city applications, yet the cost of acquiring 3D data often hinders progress. Visual localization, particularly monocular camera position estimation, offers a solution by determining the camera's pose solely
Externí odkaz:
http://arxiv.org/abs/2407.18590
Autor:
Zhu, Feiyu, Zhang, Yuming, Cai, Changpeng, He, Chenghao, Guo, Xiuyuan, Li, Jiao, Wang, Peizhe, Su, Junhao, Gao, Jialin
Local learning offers an alternative to traditional end-to-end back-propagation in deep neural networks, significantly reducing GPU memory usage. While local learning has shown promise in image classification tasks, its application to other visual ta
Externí odkaz:
http://arxiv.org/abs/2406.00446
Autor:
Xu, Mengmeng, Soldan, Mattia, Gao, Jialin, Liu, Shuming, Pérez-Rúa, Juan-Manuel, Ghanem, Bernard
Video activity localization aims at understanding the semantic content in long untrimmed videos and retrieving actions of interest. The retrieved action with its start and end locations can be used for highlight generation, temporal action detection,
Externí odkaz:
http://arxiv.org/abs/2304.02934
Autor:
Zhu Haidong, Gao Jialin
Publikováno v:
ITM Web of Conferences, Vol 26, p 01008 (2019)
Under the background of economic globalization, carrying out medical education is of great significance for improving the level of medical education of the country. The development of medical education in China has entered a new stage of development.
Externí odkaz:
https://doaj.org/article/49e7c6a70f534bc6b2fa7a105ab4b1ac
Autor:
Zhu Haidong, Gao Jialin
Publikováno v:
ITM Web of Conferences, Vol 26, p 02002 (2019)
With the rapid development of electronic computers, computer technology has been applied into various fields of medicine and its management. The application of computers in medical treatment has also greatly promoted the development of medical treatm
Externí odkaz:
https://doaj.org/article/ff5c157fda584643bb2dff4df126a2ac
Autor:
Zhang Yongrui, Gao Jialin
Publikováno v:
MATEC Web of Conferences, Vol 227, p 02001 (2018)
The rapid development and wide application of wireless network technology have brought unprecedented opportunities to the reform of medical and health services in China. Many hospitals in China have widely applied wireless network technology to infor
Externí odkaz:
https://doaj.org/article/65a03d69d3184a92bf4bdd14d59f2ed7
Autor:
Zhang Yongrui, Gao Jialin
Publikováno v:
MATEC Web of Conferences, Vol 227, p 03003 (2018)
With the advent of the Internet era, traditional teaching forms, teaching methods and teaching concepts have undergone tremendous changes, and the teaching of medical information retrieval courses has also undergone good changes. This paper will expl
Externí odkaz:
https://doaj.org/article/70fa4f1d8314479e95e1b6b8fec7095f
Moment retrieval in videos is a challenging task that aims to retrieve the most relevant video moment in an untrimmed video given a sentence description. Previous methods tend to perform self-modal learning and cross-modal interaction in a coarse man
Externí odkaz:
http://arxiv.org/abs/2205.12886