258 citations · 538 across the 39 of their papers we have counts for
39 papers
Model Merging for Medical LVLMs: A Benchmark and a Winner-Take-All Approach
Lichao Mou, Shilan Zhang, Chunlei Li +7
Large vision-language models (LVLMs) can be adapted to specialized medical imaging tasks via parameter-efficient fine-tuning approaches such as low-rank adaptation (LoRA), leading…
Towards Real-World Ultrasound Understanding: Large Vision-Language Models from Multi-Image Examinations with Long-Form Reports
Bingcong Yan, Chunlei Li, Jingliang Hu +3
Large vision-language models (LVLMs) have achieved strong performance across many medical imaging tasks, yet their application to ultrasound remains limited due to its inherent com…
On Revisiting Entropy for Identifying Mislabeled Images
Chunlei Li, Zixuan Zheng, Yilei Shi +5
Mislabeled samples in training datasets severely degrade the performance of deep networks, as overparameterized models tend to memorize erroneous labels. We address this challenge…
Learning Domain-Aware Task Prompt Representations for Multi-Domain All-in-One Image Restoration
Guanglu Dong, Chunlei Li, Chao Ren +4
Recently, significant breakthroughs have been made in all-in-one image restoration (AiOIR), which can handle multiple restoration tasks with a single model. However, existing metho…
Multitask Learning for Earth Observation Data Classification with Hybrid Quantum Network
Fan Fan, Yilei Shi, Tobias Guggemos +1
Quantum machine learning (QML) has gained increasing attention as a potential solution to address the challenges of computation requirements in the future. Earth observation (EO) h…
A Deep Dive into OpenStreetMap Research Since its Inception (2008-2024): Contributors, Topics, and Future Trends
Yao Sun, Liqiu Meng, Andres Camero +2
OpenStreetMap (OSM) has transitioned from a pioneering volunteered geographic information (VGI) project into a global, multi-disciplinary research nexus. This study presents a bibl…
GlobalBuildingAtlas: An Open Global and Complete Dataset of Building Polygons, Heights and LoD1 3D Models
Xiao Xiang Zhu, Sining Chen, Fahong Zhang +2
We introduce GlobalBuildingAtlas, a publicly available dataset providing global and complete coverage of building polygons, heights and Level of Detail 1 (LoD1) 3D building models.…
GlobalGeoTree: A Multi-Granular Vision-Language Dataset for Global Tree Species Classification
Yang Mu, Zhitong Xiong, Yi Wang +5
Global tree species mapping using remote sensing data is vital for biodiversity monitoring, forest management, and ecological research. However, progress in this field has been con…
CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention
Yaxiong Chen, Minghong Wei, Zixuan Zheng +5
Referring medical image segmentation targets delineating lesions indicated by textual descriptions. Aligning visual and textual cues is challenging due to their distinct data prope…
Global High Categorical Resolution Land Cover Mapping via Weak Supervision
Xin-Yi Tong, Runmin Dong, Xiao Xiang Zhu
Land cover information is indispensable for advancing the United Nations' sustainable development goals, and land cover mapping under a more detailed category system would signific…
GlobalBuildingMap -- Unveiling the Mystery of Global Buildings
Xiao Xiang Zhu, Qingyu Li, Yilei Shi +3
Understanding how buildings are distributed globally is crucial to revealing the human footprint on our home planet. This built environment affects local climate, land surface albe…
Large-scale flood modeling and forecasting with FloodCast
Qingsong Xu, Yilei Shi, Jonathan Bamber +2
Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to a…
ChatEarthNet: A Global-Scale Image-Text Dataset Empowering Vision-Language Geo-Foundation Models
Zhenghang Yuan, Zhitong Xiong, Lichao Mou +1
An in-depth comprehension of global land cover is essential in Earth observation, forming the foundation for a multitude of applications. Although remote sensing technology has adv…
Efficient Subseasonal Weather Forecast using Teleconnection-informed Transformers
Shan Zhao, Zhitong Xiong, Xiao Xiang Zhu
Subseasonal forecasting, which is pivotal for agriculture, water resource management, and early warning of disasters, faces challenges due to the chaotic nature of the atmosphere.…
Task Specific Pretraining with Noisy Labels for Remote Sensing Image Segmentation
Chenying Liu, Conrad M Albrecht, Yi Wang +1
Compared to supervised deep learning, self-supervision provides remote sensing a tool to reduce the amount of exact, human-crafted geospatial annotations. While image-level informa…
One for All: Toward Unified Foundation Models for Earth Vision
Zhitong Xiong, Yi Wang, Fahong Zhang +1
Foundation models characterized by extensive parameters and trained on large-scale datasets have demonstrated remarkable efficacy across various downstream tasks for remote sensing…
Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty
Katharina Hechinger, Christoph Koller, Xiao Xiang Zhu +1
Uncertainty in machine learning models is a timely and vast field of research. In supervised learning, uncertainty can already occur in the first stage of the training process, the…
Categorising the World into Local Climate Zones -- Towards Quantifying Labelling Uncertainty for Machine Learning Models
Katharina Hechinger, Xiao Xiang Zhu, Göran Kauermann
Image classification is often prone to labelling uncertainty. To generate suitable training data, images are labelled according to evaluations of human experts. This can result in…
Deep Semantic Model Fusion for Ancient Agricultural Terrace Detection
Yi Wang, Chenying Liu, Arti Tiwari +4
Discovering ancient agricultural terraces in desert regions is important for the monitoring of long-term climate changes on the Earth's surface. However, traditional ground surveys…
Semi-Supervised Learning for hyperspectral images by non parametrically predicting view assignment
Shivam Pande, Nassim Ait Ali Braham, Yi Wang +3
Hyperspectral image (HSI) classification is gaining a lot of momentum in present time because of high inherent spectral information within the images. However, these images suffer…
DisasterNets: Embedding Machine Learning in Disaster Mapping
Qingsong Xu, Yilei Shi, Xiao Xiang Zhu
Disaster mapping is a critical task that often requires on-site experts and is time-consuming. To address this, a comprehensive framework is presented for fast and accurate recogni…
The Politics of Language Choice: How the Russian-Ukrainian War Influences Ukrainians' Language Use on Twitter
Daniel Racek, Brittany I. Davidson, Paul W. Thurner +2
The use of language is innately political and often a vehicle of cultural identity as well as the basis for nation building. Here, we examine language choice and tweeting activity…
Overcoming Language Bias in Remote Sensing Visual Question Answering via Adversarial Training
Zhenghang Yuan, Lichao Mou, Xiao Xiang Zhu
The Visual Question Answering (VQA) system offers a user-friendly interface and enables human-computer interaction. However, VQA models commonly face the challenge of language bias…
GAMUS: A Geometry-aware Multi-modal Semantic Segmentation Benchmark for Remote Sensing Data
Zhitong Xiong, Sining Chen, Yi Wang +2
Geometric information in the normalized digital surface models (nDSM) is highly correlated with the semantic class of the land cover. Exploiting two modalities (RGB and nDSM (heigh…