activity
20202024
most citedDiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model

9 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

SMamba: A Spatial-spectral State Space Model for Hyperspectral Image Classification

Guanchun Wang, Xiangrong Zhang, Zelin Peng +2

Land cover analysis using hyperspectral images (HSI) remains an open problem due to their low spatial resolution and complex spectral information. Recent studies are primarily dedi…

cs.CV20235 cited

Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances

Xiangrong Zhang, Tianyang Zhang, Guanchun Wang +4

Remote sensing object detection (RSOD), one of the most fundamental and challenging tasks in the remote sensing field, has received longstanding attention. In recent years, deep le…

cs.CV20214 cited

Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation

Xiangrong Zhang, Zelin Peng, Peng Zhu +4

Semantic segmentation has been continuously investigated in the last ten years, and majority of the established technologies are based on supervised models. In recent years, image-…

cs.CV2021

Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Images

Tianyang Zhang, Xiangrong Zhang, Peng Zhu +4

In this paper, we focus on the challenging multicategory instance segmentation problem in remote sensing images (RSIs), which aims at predicting the categories of all instances and…

q-bio.QM2020

OpenHI2 -- Open source histopathological image platform

Pargorn Puttapirat, Haichuan Zhang, Jingyi Deng +7

Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological…

eess.IV2020

Effects of annotation granularity in deep learning models for histopathological images

Jiangbo Shi, Zeyu Gao, Haichuan Zhang +4

Pathological is crucial to cancer diagnosis. Usually, Pathologists draw their conclusion based on observed cell and tissue structure on histology slides. Rapid development in machi…