Rizwan Qureshi — accepted AI-conference papers

2026

DINOv3-Powered Multi-Task Foundation Model for Quantitative Remote Sensing Estimation (Student Abstract)

Zhenyu Yu, Mohd Yamani Idna Idris, Pei Wang, Rizwan Qureshi

AAAI 2026technical

Quantitative remote sensing estimation is critical for environmental monitoring, providing continuous measures of vegetation indices, canopy height, and carbon stock. Traditional radiative-transfer models and empirical regressions require expert knowledge and generalize poorly, while deep learning m

Cited by 0 Source ↗PDF ↗Scholar ↗

2025

Test-Time Retrieval-Augmented Adaptation for Vision-Language Models

Xinqi Fan, Xueli Chen, Luoxiao Yang, Chuin Hong Yap, Rizwan Qureshi, Qi Dou +2

ICCV 2025poster

Vision-language models (VLMs) have shown promise in test-time adaptation tasks due to their remarkable capabilities in understanding and reasoning about visual content through natural language descriptions. However, training VLMs typically demands substantial computational resources, and they often…

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗