1 citations · 1 across the 5 of their papers we have counts for
5 papers
Semi-supervised Source Detection in Astronomical Images: New Benchmark and Strong Baseline
Longhan Feng, Zihuang Cao, Ali Luo +5
Source detection in modern observational astronomy is a cornerstone for localizing and identifying stellar sources accurately. It is crucial for studies such as stellar population…
Spec-o3: A Tool-Augmented Vision-Language Agent for Rare Celestial Object Candidate Vetting via Automated Spectral Inspection
Minghui Jia, Qichao Zhang, Ali Luo +5
Due to the limited generalization and interpretability of deep learning classifiers, The final vetting of rare celestial object candidates still relies on expert visual inspection-…
StellarF: A Physics-Informed LoRA Framework for Stellar Flare Forecasting with Historical & Statistical Data
Tianyu Su, Zhiqiang Zou, Qingyu Lu +4
Stellar flare forecasting represents a critical frontier in astrophysics, offering profound insights into stellar activity mechanisms and exoplanetary habitability assessments. Yet…
FLARE: A Framework for Stellar Flare Forecasting using Stellar Physical Properties and Historical Records
Bingke Zhu, Xiaoxiao Wang, Minghui Jia +6
Stellar flare events are critical observational samples for astronomical research; however, recorded flare events remain limited. Stellar flare forecasting can provide additional f…
Technique Report of CVPR 2024 PBDL Challenges
Ying Fu, Yu Li, Shaodi You +96
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…