75 citations · 147 across the 11 of their papers we have counts for
11 papers
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…
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…
DiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model
Xiangrong Zhang, Shunli Tian, Guanchun Wang +2
Hyperspectral image change detection (HSI-CD) has emerged as a crucial research area in remote sensing due to its ability to detect subtle changes on the earth's surface. Recently,…
SoftMatch Distance: A Novel Distance for Weakly-Supervised Trend Change Detection in Bi-Temporal Images
Yuqun Yang, Xu Tang, Xiangrong Zhang +2
General change detection (GCD) and semantic change detection (SCD) are common methods for identifying changes and distinguishing object categories involved in those changes, respec…
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information
Guanchun Wang, Xiangrong Zhang, Zelin Peng +3
Weakly supervised object detection (WSOD) is a challenging task, in which image-level labels (e.g., categories of the instances in the whole image) are used to train an object dete…
MidNet: An Anchor-and-Angle-Free Detector for Oriented Ship Detection in Aerial Images
Feng Jie, Yuping Liang, Junpeng Zhang +3
Ship detection in aerial images remains an active yet challenging task due to arbitrary object orientation and complex background from a bird's-eye perspective. Most of the existin…
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-…
Unsupervised Outlier Detection using Memory and Contrastive Learning
Ning Huyan, Dou Quan, Xiangrong Zhang +3
Outlier detection is one of the most important processes taken to create good, reliable data in machine learning. The most methods of outlier detection leverage an auxiliary recons…
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…
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…
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…