4 papers
Can We Enhance the Quality of Mobile Crowdsensing Data Without Ground Truth?
Jiajie Li, Bo Gu, Shimin Gong +2
Mobile crowdsensing (MCS) has emerged as a prominent trend across various domains. However, ensuring the quality of the sensing data submitted by mobile users (MUs) remains a compl…
CosmoCLIP: Generalizing Large Vision-Language Models for Astronomical Imaging
Raza Imam, Mohammed Talha Alam, Umaima Rahman +2
Existing vision-text contrastive learning models enhance representation transferability and support zero-shot prediction by matching paired image and caption embeddings while pushi…
AstroSpy: On detecting Fake Images in Astronomy via Joint Image-Spectral Representations
Mohammed Talha Alam, Raza Imam, Mohsen Guizani +1
The prevalence of AI-generated imagery has raised concerns about the authenticity of astronomical images, especially with advanced text-to-image models like Stable Diffusion produc…
FLARE up your data: Diffusion-based Augmentation Method in Astronomical Imaging
Mohammed Talha Alam, Raza Imam, Mohsen Guizani +1
The intersection of Astronomy and AI encounters significant challenges related to issues such as noisy backgrounds, lower resolution (LR), and the intricate process of filtering an…