Zobrazeno 1 - 10
of 5 871
pro vyhledávání: '"Tong-Xin An"'
Publikováno v:
PeerJ, Vol 11, p e14933 (2023)
Nitrogen (N) is an important macronutrient and is comprehensively involved in the synthesis of secondary metabolites. However, the interaction between N supply and crop yield and the accumulation of effective constituents in an N-sensitive medicinal
Externí odkaz:
https://doaj.org/article/a70f86dcaf0b49988eb78e739c1d1d4c
Autor:
Zhu Cun, Xiang-Zeng Xu, Jin-Yan Zhang, Sheng-Pu Shuang, Hong-Min Wu, Tong-Xin An, Jun-Wen Chen
Publikováno v:
Frontiers in Plant Science, Vol 13 (2023)
Photosynthetic adaptive strategies vary with the growth irradiance. The potential photosynthetic adaptive strategies of shade-tolerant species Panax notoginseng (Burkill) F. H. Chen to long-term high light and low light remains unclear. Photosyntheti
Externí odkaz:
https://doaj.org/article/05d8e5ed49b1488c86c11693b7398789
In spatial design, Artificial Intelligence (AI) tools often generate the entire spatial design outcome in a single automated step, rather than engaging users in a deepening and iterative process. This significantly reduces users' involvement, learnin
Externí odkaz:
http://arxiv.org/abs/2410.20124
Autor:
Wang, Ruicheng, Xu, Sicheng, Dai, Cassie, Xiang, Jianfeng, Deng, Yu, Tong, Xin, Yang, Jiaolong
We present MoGe, a powerful model for recovering 3D geometry from monocular open-domain images. Given a single image, our model directly predicts a 3D point map of the captured scene with an affine-invariant representation, which is agnostic to true
Externí odkaz:
http://arxiv.org/abs/2410.19115
Distributions in spatial model often exhibit localized features. Intuitively, this locality implies a low intrinsic dimensionality, which can be exploited for efficient approximation and computation of complex distributions. However, existing approxi
Externí odkaz:
http://arxiv.org/abs/2410.11771
Selective state space models (SSM), such as Mamba, have gained prominence for their effectiveness in modeling sequential data. Despite their outstanding empirical performance, a comprehensive theoretical understanding of deep selective SSM remains el
Externí odkaz:
http://arxiv.org/abs/2410.03292
Stochastic gradient descent (SGD) is a powerful optimization technique that is particularly useful in online learning scenarios. Its convergence analysis is relatively well understood under the assumption that the data samples are independent and ide
Externí odkaz:
http://arxiv.org/abs/2410.01195
Dynamic mode decomposition (DMD) is a data-driven method of extracting spatial-temporal coherent modes from complex systems and providing an equation-free architecture to model and predict systems. However, in practical applications, the accuracy of
Externí odkaz:
http://arxiv.org/abs/2410.02815
In whiteboard-based remote communication, the seamless integration of drawn content and hand-screen interactions is essential for an immersive user experience. Previous methods either require bulky device setups for capturing hand gestures or fail to
Externí odkaz:
http://arxiv.org/abs/2409.13347
We consider Bayesian inference for image deblurring with total variation (TV) prior. Since the posterior is analytically intractable, we resort to Markov chain Monte Carlo (MCMC) methods. However, since most MCMC methods significantly deteriorate in
Externí odkaz:
http://arxiv.org/abs/2409.09810