Zobrazeno 1 - 10
of 1 263
pro vyhledávání: '"SUN, Guodong"'
Atmospheric turbulence introduces severe spatial and geometric distortions, challenging traditional image restoration methods. We propose the Probabilistic Prior Turbulence Removal Network (PPTRN), which combines probabilistic diffusion-based prior m
Externí odkaz:
http://arxiv.org/abs/2411.10321
Self-supervised monocular depth estimation aims to infer depth information without relying on labeled data. However, the lack of labeled information poses a significant challenge to the model's representation, limiting its ability to capture the intr
Externí odkaz:
http://arxiv.org/abs/2406.08928
Recently there has been a growing interest in industry and academia, regarding the use of wireless chargers to prolong the operational longevity of unmanned aerial vehicles (commonly knowns as drones). In this paper we consider a charger-assisted dro
Externí odkaz:
http://arxiv.org/abs/2403.10761
Autor:
Sun, Guodong, Peng, Yuting, Cheng, Le, Xu, Mengya, Wang, An, Wu, Bo, Ren, Hongliang, Zhang, Yang
The precise segmentation of ore images is critical to the successful execution of the beneficiation process. Due to the homogeneous appearance of the ores, which leads to low contrast and unclear boundaries, accurate segmentation becomes challenging,
Externí odkaz:
http://arxiv.org/abs/2402.17370
Image segmentation methods have been utilized to determine the particle size distribution of crushed ores. Due to the complex working environment, high-powered computing equipment is difficult to deploy. At the same time, the ore distribution is stac
Externí odkaz:
http://arxiv.org/abs/2311.05929
The reconfigurable intelligent surface (RIS) technology allows one to engineer spatial diversity in complex cellular networks. This paper provides a framework for the system-level performance assessment of RIS-assisted networks and in particular down
Externí odkaz:
http://arxiv.org/abs/2310.06754
Efficient RGB-D semantic segmentation has received considerable attention in mobile robots, which plays a vital role in analyzing and recognizing environmental information. According to previous studies, depth information can provide corresponding ge
Externí odkaz:
http://arxiv.org/abs/2308.06024
Efficient visual fault detection of freight trains is a critical part of ensuring the safe operation of railways under the restricted hardware environment. Although deep learning-based approaches have excelled in object detection, the efficiency of f
Externí odkaz:
http://arxiv.org/abs/2307.00701
For the ore particle size detection, obtaining a sizable amount of high-quality ore labeled data is time-consuming and expensive. General object detection methods often suffer from severe over-fitting with scarce labeled data. Despite their ability t
Externí odkaz:
http://arxiv.org/abs/2305.01183
Publikováno v:
Industrial Lubrication and Tribology, 2024, Vol. 76, Issue 3, pp. 431-440.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/ILT-09-2023-0304
