Zobrazeno 1 - 10
of 3 392
pro vyhledávání: '"WANG, CE"'
Remote-sensing (RS) image compression at extremely low bitrates has always been a challenging task in practical scenarios like edge device storage and narrow bandwidth transmission. Generative models including VAEs and GANs have been explored to comp
Externí odkaz:
http://arxiv.org/abs/2409.01935
Image rescaling aims to learn the optimal downscaled low-resolution (LR) image that can be accurately reconstructed to its original high-resolution (HR) counterpart. This process is crucial for efficient image processing and storage, especially in th
Externí odkaz:
http://arxiv.org/abs/2408.09151
Autor:
Tian, Ye, Zhao, Yajuan, Wu, Yue, Ye, Jilai, Mei, Shuyao, Chi, Zhihao, Tian, Tian, Wang, Ce, Shi, Zhe-Yu, Chen, Yu, Hu, Jiazhong, Zhai, Hui, Chen, Wenlan
We report the first experimental observation of dissipation-driven coherent quantum many-body oscillation, and this oscillation is manifested as the coherent exchange of atoms between the thermal and the condensate components in a three-dimensional p
Externí odkaz:
http://arxiv.org/abs/2408.03815
Identifying and classifying quantum phases from measurable time series in many-body dynamics have significant values, yet face formidable challenges, requiring profound knowledge of physicists. Here, to achieve a pure data-driven machine intelligent
Externí odkaz:
http://arxiv.org/abs/2407.17266
Large parallax between images is an intractable issue in image stitching. Various warping-based methods are proposed to address it, yet the results are unsatisfactory. In this paper, we propose a novel image stitching method using multi-homography wa
Externí odkaz:
http://arxiv.org/abs/2406.19922
Autor:
Wang, Ce, Sun, Wanjie
Remote sensing images captured by different platforms exhibit significant disparities in spatial resolution. Large scale factor super-resolution (SR) algorithms are vital for maximizing the utilization of low-resolution (LR) satellite data captured f
Externí odkaz:
http://arxiv.org/abs/2405.07044
The work intends to extend the moir\'e physics to three dimensions. Three-dimensional moir\'e patterns can be realized in ultracold atomic gases by coupling two spin states in spin-dependent optical lattices with a relative twist, a structure current
Externí odkaz:
http://arxiv.org/abs/2404.19608
Physics--informed neural networks (PINN) have shown their potential in solving both direct and inverse problems of partial differential equations. In this paper, we introduce a PINN-based deep learning approach to reconstruct one-dimensional rough su
Externí odkaz:
http://arxiv.org/abs/2404.14984
The deep connection among braids, knots and topological physics has provided valuable insights into studying topological states in various physical systems. However, identifying distinct braid groups and knot topology embedded in non-Hermitian system
Externí odkaz:
http://arxiv.org/abs/2401.10908
Emerging neural reconstruction techniques based on tomography (e.g., NeRF, NeAT, and NeRP) have started showing unique capabilities in medical imaging. In this work, we present a novel Polychromatic neural representation (Polyner) to tackle the chall
Externí odkaz:
http://arxiv.org/abs/2306.15203