1 citations · 1 across the 2 of their papers we have counts for
4 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…
MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery
Qinfeng Zhu, Yuan Fang, Lei Fan
Crack detection is a critical task in structural health monitoring, aimed at assessing the structural integrity of bridges, buildings, and roads to prevent potential failures. Visi…
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…