Zobrazeno 1 - 10
of 382
pro vyhledávání: '"Xu Tingfa"'
Publikováno v:
Nanophotonics, Vol 13, Iss 20, Pp 3883-3893 (2024)
Spectral reconstruction, critical for understanding sample composition, is extensively applied in fields like remote sensing, geology, and medical imaging. However, existing spectral reconstruction methods require bulky equipment or complex electroni
Externí odkaz:
https://doaj.org/article/26375d2d959641fa9a50d2aaa0055fe5
Publikováno v:
Nanophotonics, Vol 13, Iss 18, Pp 3599-3607 (2024)
Miniature spectrometer is powerful tool for scientific research and industrial inspection. Here, we report the fabrication of graded perovskite filters with tunable bandgap and their application in constructing miniature spectrometer. The graded pero
Externí odkaz:
https://doaj.org/article/5355b08c24d540f29537956e547a3a20
Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions
Achieving robust 3D perception in the face of corrupted data presents an challenging hurdle within 3D vision research. Contemporary transformer-based point cloud recognition models, albeit advanced, tend to overfit to specific patterns, consequently
Externí odkaz:
http://arxiv.org/abs/2411.00462
Autor:
Huang, Shiqi, Xu, Tingfa, Shen, Ziyi, Saeed, Shaheer Ullah, Yan, Wen, Barratt, Dean, Hu, Yipeng
This paper describes a new spatial correspondence representation based on paired regions-of-interest (ROIs), for medical image registration. The distinct properties of the proposed ROI-based correspondence are discussed, in the context of potential b
Externí odkaz:
http://arxiv.org/abs/2410.14083
Extracting discriminative information from complex spectral details in hyperspectral image (HSI) for HSI classification is pivotal. While current prevailing methods rely on spectral magnitude features, they could cause confusion in certain classes, r
Externí odkaz:
http://arxiv.org/abs/2407.18593
Hyperspectral image classification, a task that assigns pre-defined classes to each pixel in a hyperspectral image of remote sensing scenes, often faces challenges due to the neglect of correlations between spectrally similar pixels. This oversight c
Externí odkaz:
http://arxiv.org/abs/2407.07307
Autor:
Huang, Shiqi, Xu, Tingfa, Shen, Ziyi, Saeed, Shaheer Ullah, Yan, Wen, Barratt, Dean, Hu, Yipeng
The goal of image registration is to establish spatial correspondence between two or more images, traditionally through dense displacement fields (DDFs) or parametric transformations (e.g., rigid, affine, and splines). Rethinking the existing paradig
Externí odkaz:
http://arxiv.org/abs/2405.10879
Hyperspectral salient object detection (HSOD) has exhibited remarkable promise across various applications, particularly in intricate scenarios where conventional RGB-based approaches fall short. Despite the considerable progress in HSOD method advan
Externí odkaz:
http://arxiv.org/abs/2404.00694
In the realm of unmanned aerial vehicle (UAV) tracking, Siamese-based approaches have gained traction due to their optimal balance between efficiency and precision. However, UAV scenarios often present challenges such as insufficient sampling resolut
Externí odkaz:
http://arxiv.org/abs/2403.04363
Noisy labels, inevitably existing in pseudo segmentation labels generated from weak object-level annotations, severely hampers model optimization for semantic segmentation. Previous works often rely on massive hand-crafted losses and carefully-tuned
Externí odkaz:
http://arxiv.org/abs/2401.11738