57 citations · 353 across the 50 of their papers we have counts for
15 papers · 1 filter
DYffCast: Regional Precipitation Nowcasting Using IMERG Satellite Data. A case study over South America
Daniel Seal, Rossella Arcucci, Salva Rühling-Cachay +1
Climate change is increasing the frequency of extreme precipitation events, making weather disasters such as flooding and landslides more likely. The ability to accurately nowcast…
Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data
Bo Pang, Sibo Cheng, Yuhan Huang +5
Predicting the extent of massive wildfires once ignited is essential to reduce the subsequent socioeconomic losses and environmental damage, but challenging because of the complexi…
How Does Diverse Interpretability of Textual Prompts Impact Medical Vision-Language Zero-Shot Tasks?
Sicheng Wang, Che Liu, Rossella Arcucci
Recent advancements in medical vision-language pre-training (MedVLP) have significantly enhanced zero-shot medical vision tasks such as image classification by leveraging large-sca…
Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?
Che Liu, Zhongwei Wan, Haozhe Wang +6
Medical Vision-Language Pre-training (MedVLP) has made significant progress in enabling zero-shot tasks for medical image understanding. However, training MedVLP models typically r…
FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks
Peiran Wu, Che Liu, Canyu Chen +3
Advancements in Multimodal Large Language Models (MLLMs) have significantly improved medical task performance, such as Visual Question Answering (VQA) and Report Generation (RG). H…
TorchDA: A Python package for performing data assimilation with deep learning forward and transformation functions
Sibo Cheng, Jinyang Min, Che Liu +1
Data assimilation techniques are often confronted with challenges handling complex high dimensional physical systems, because high precision simulation in complex high dimensional…
Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale
Sibo Cheng, Hector Chassagnon, Matthew Kasoar +2
Global wildfire models play a crucial role in anticipating and responding to changing wildfire regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire emis…
Argus: Benchmarking and Enhancing Vision-Language Models for 3D Radiology Report Generation
Che Liu, Zhongwei Wan, Yuqi Wang +5
Automatic radiology report generation holds significant potential to streamline the labor-intensive process of report writing by radiologists, particularly for 3D radiographs such…
BIMCV-R: A Landmark Dataset for 3D CT Text-Image Retrieval
Yinda Chen, Che Liu, Xiaoyu Liu +2
The burgeoning integration of 3D medical imaging into healthcare has led to a substantial increase in the workload of medical professionals. To assist clinicians in their diagnosti…
Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
Che Liu, Zhongwei Wan, Cheng Ouyang +3
Electrocardiograms (ECGs) are non-invasive diagnostic tools crucial for detecting cardiac arrhythmic diseases in clinical practice. While ECG Self-supervised Learning (eSSL) method…
MEIT: Multimodal Electrocardiogram Instruction Tuning on Large Language Models for Report Generation
Zhongwei Wan, Che Liu, Xin Wang +6
Electrocardiogram (ECG) is the primary non-invasive diagnostic tool for monitoring cardiac conditions and is crucial in assisting clinicians. Recent studies have concentrated on cl…
Explainable Global Wildfire Prediction Models using Graph Neural Networks
Dayou Chen, Sibo Cheng, Jinwei Hu +2
Wildfire prediction has become increasingly crucial due to the escalating impacts of climate change. Traditional CNN-based wildfire prediction models struggle with handling missing…
Multi-fidelity physics constrained neural networks for dynamical systems
Hao Zhou, Sibo Cheng, Rossella Arcucci
Physics-constrained neural networks are commonly employed to enhance prediction robustness compared to purely data-driven models, achieved through the inclusion of physical constra…
Data Assimilation using ERA5, ASOS, and the U-STN model for Weather Forecasting over the UK
Wenqi Wang, Jacob Bieker, Rossella Arcucci +1
In recent years, the convergence of data-driven machine learning models with Data Assimilation (DA) offers a promising avenue for enhancing weather forecasting. This study delves i…
Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training
Jiuming Qin, Che Liu, Sibo Cheng +2
Modern healthcare often utilises radiographic images alongside textual reports for diagnostics, encouraging the use of Vision-Language Self-Supervised Learning (VL-SSL) with large…