Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Huang, Zhanchao"'
Publikováno v:
IEEE IGARSS 2024
The recognition of sea ice is of great significance for reflecting climate change and ensuring the safety of ship navigation. Recently, many deep learning based methods have been proposed and applied to segment and recognize sea ice regions. However,
Externí odkaz:
http://arxiv.org/abs/2405.13197
In large-scale disaster events, the planning of optimal rescue routes depends on the object detection ability at the disaster scene, with one of the main challenges being the presence of dense and occluded objects. Existing methods, which are typical
Externí odkaz:
http://arxiv.org/abs/2405.08251
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, 2022
A few lightweight convolutional neural network (CNN) models have been recently designed for remote sensing object detection (RSOD). However, most of them simply replace vanilla convolutions with stacked separable convolutions, which may not be effici
Externí odkaz:
http://arxiv.org/abs/2209.07709
Publikováno v:
Transactions on Geoscience and Remote Sensing, 2022
Arbitrary-oriented object detection (AOOD) plays a significant role for image understanding in remote sensing scenarios. The existing AOOD methods face the challenges of ambiguity and high costs in angle representation. To this end, a multi-grained a
Externí odkaz:
http://arxiv.org/abs/2209.02884
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems,2024
Arbitrary-oriented object detection (AOOD) has been widely applied to locate and classify objects with diverse orientations in remote sensing images. However, the inconsistent features for the localization and classification tasks in AOOD models may
Externí odkaz:
http://arxiv.org/abs/2209.02200
Publikováno v:
2022IGARSS
Infrared small target detection (ISTD) has attracted widespread attention and been applied in various fields. Due to the small size of infrared targets and the noise interference from complex backgrounds, the performance of ISTD using convolutional n
Externí odkaz:
http://arxiv.org/abs/2206.02120
Autor:
Chen, Zequn, Li, Xiaojing, Tang, Yiheng, Huang, Zhanchao, Huang, Ji, Liu, Haoran, Weng, Yang, Zhu, Yue, Zhao, Jingyang, Tang, Renjie, Liu, Zhu, Bao, Kangjian, Jian, Jialing, Ye, Yuting, Yun, Yiting, Wang, Lichun, Guo, Chengchen, Lin, Hongtao, Jiang, Hanqing, Si, Ke, Gong, Wei, Li, Lan
Publikováno v:
In Cell Reports Physical Science 16 October 2024 5(10)
Publikováno v:
In ISPRS Journal of Photogrammetry and Remote Sensing December 2024 218 Part A:389-404
Publikováno v:
IEEE Transactions on Image Processing 2022
Recently, many arbitrary-oriented object detection (AOOD) methods have been proposed and attracted widespread attention in many fields. However, most of them are based on anchor-boxes or standard Gaussian heatmaps. Such label assignment strategy may
Externí odkaz:
http://arxiv.org/abs/2109.12848
Publikováno v:
In Infrared Physics and Technology August 2023 132