64 citations · 98 across the 10 of their papers we have counts for
10 papers
A generalised pre-training strategy for deep learning networks in semantic segmentation of remotely sensed images
Yuan Fang, Yuanzhi Cai, Jagannath Aryal +4
In the segmentation of remotely sensed images, deep learning models are typically pre-trained using large image databases like ImageNet before fine-tuned on domain-specific dataset…
Evaluating the Impact of Point Cloud Colorization on Semantic Segmentation Accuracy
Qinfeng Zhu, Jiaze Cao, Yuanzhi Cai +1
Point cloud semantic segmentation, the process of classifying each point into predefined categories, is essential for 3D scene understanding. While image-based segmentation is wide…
WALLABY Pilot Survey: HI source-finding with a machine learning framework
Li Wang, O. Ivy Wong, Tobias Westmeier +10
The data volumes generated by the WALLABY atomic Hydrogen (HI) survey using the Australiian Square Kilometre Array Pathfinder (ASKAP) necessitate greater automation and reliable au…
Enhancing Environmental Monitoring through Multispectral Imaging: The WasteMS Dataset for Semantic Segmentation of Lakeside Waste
Qinfeng Zhu, Ningxin Weng, Lei Fan +1
Environmental monitoring of lakeside green areas is crucial for environmental protection. Compared to manual inspections, computer vision technologies offer a more efficient soluti…
Seg-LSTM: Performance of xLSTM for Semantic Segmentation of Remotely Sensed Images
Qinfeng Zhu, Yuanzhi Cai, Lei Fan
Recent advancements in autoregressive networks with linear complexity have driven significant research progress, demonstrating exceptional performance in large language models. A r…
Rethinking Scanning Strategies with Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study
Qinfeng Zhu, Yuan Fang, Yuanzhi Cai +2
Deep learning methods, especially Convolutional Neural Networks (CNN) and Vision Transformer (ViT), are frequently employed to perform semantic segmentation of high-resolution remo…
Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model
Qinfeng Zhu, Yuanzhi Cai, Yuan Fang +4
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…
SDRCNN: A single-scale dense residual connected convolutional neural network for pansharpening
Yuan Fang, Yuanzhi Cai, Lei Fan
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.…
OSTA: One-shot Task-adaptive Channel Selection for Semantic Segmentation of Multichannel Images
Yuanzhi Cai, Jagannath Aryal, Yuan Fang +2
Semantic segmentation of multichannel images is a fundamental task for many applications. Selecting an appropriate channel combination from the original multichannel image can impr…
SBSS: Stacking-Based Semantic Segmentation Framework for Very High Resolution Remote Sensing Image
Yuanzhi Cai, Lei Fan, Yuan Fang
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 V…