Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Cai, Yuanzhi"'
Autor:
Wang, Li, Wong, O. Ivy, Westmeier, Tobias, Murugeshan, Chandrashekar, Lee-Waddell, Karen, Cai, Yuanzhi., Liu, Xiu., Shen, Austin Xiaofan, Rhee, Jonghwan, Dénes, Helga, Deg, Nathan, Kamphuis, Peter, Catinella, Barbara
The data volumes generated by the WALLABY atomic Hydrogen (HI) survey using the Australiian Square Kilometre Array Pathfinder (ASKAP) necessitate greater automation and reliable automation in the task of source-finding and cataloguing. To this end, w
Externí odkaz:
http://arxiv.org/abs/2409.11668
Environmental monitoring of lakeside green areas is crucial for environmental protection. Compared to manual inspections, computer vision technologies offer a more efficient solution when deployed on-site. Multispectral imaging provides diverse infor
Externí odkaz:
http://arxiv.org/abs/2407.17028
Recent advancements in autoregressive networks with linear complexity have driven significant research progress, demonstrating exceptional performance in large language models. A representative model is the Extended Long Short-Term Memory (xLSTM), wh
Externí odkaz:
http://arxiv.org/abs/2406.14086
Deep learning methods, especially Convolutional Neural Networks (CNN) and Vision Transformer (ViT), are frequently employed to perform semantic segmentation of high-resolution remotely sensed images. However, CNNs are constrained by their restricted
Externí odkaz:
http://arxiv.org/abs/2405.08493
High-resolution remotely sensed images pose a challenge for commonly used semantic segmentation methods such as Convolutional Neural Network (CNN) and Vision Transformer (ViT). CNN-based methods struggle with handling such high-resolution images due
Externí odkaz:
http://arxiv.org/abs/2404.01705
Pansharpening is a process of fusing a high spatial resolution panchromatic image and a low spatial resolution multispectral image to create a high-resolution multispectral image. A novel single-branch, single-scale lightweight convolutional neural n
Externí odkaz:
http://arxiv.org/abs/2307.00327
Semantic segmentation of multichannel images is a fundamental task for many applications. Selecting an appropriate channel combination from the original multichannel image can improve the accuracy of semantic segmentation and reduce the cost of data
Externí odkaz:
http://arxiv.org/abs/2305.04766
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, 2023
Semantic segmentation of Very High Resolution (VHR) remote sensing images is a fundamental task for many applications. However, large variations in the scales of objects in those VHR images pose a challenge for performing accurate semantic segmentati
Externí odkaz:
http://arxiv.org/abs/2212.07623
Publikováno v:
In Automation in Construction February 2024 158
Autor:
Gong, Puyue, Cai, Yuanzhi, Chen, Bing, Zhang, Cheng, Stravoravdis, Spyros, Sharples, Stephen, Ban, Qichao, Yu, Yuehong
Publikováno v:
In Journal of Building Engineering 1 December 2023 80