collaborators

6 papers

cs.CV2026

GeoDisaster: Benchmarking Orchestrated Agents for Operational Disaster Geo-Intelligence

Maram Hasan, Aman Verma, Savitra Roy +5

Remote-sensing vision-language models (RS-VLMs) have advanced Earth-observation analysis toward visual interpretation and instruction-following, yet fall short of operational geo-i…

cs.LG2026

GCA Framework: A GCC Countries-Grounded Dataset and Agentic Pipeline for Climate Decision Support

Muhammad Umer Sheikh, Khawar Shehzad, Salman Khan +2

Climate decision-making in the GCC states increasingly demands systems that can translate heterogeneous scientific and policy evidence into actionable guidance, yet general-purpose…

cs.CV2026

BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs

Mainak Singha, Tanisha Gupta, Ankit Jha +3

Pretrained biomedical vision-language models (VLMs) such as BioMedCLIP perform well on average but often degrade on challenging modalities where inter-class margins are small and a…

cs.CV2026

GeoMeld: Toward Semantically Grounded Foundation Models for Remote Sensing

Maram Hasan, Md Aminur Hossain, Savitra Roy +6

Effective foundation modeling in remote sensing requires spatially aligned heterogeneous modalities coupled with semantically grounded supervision, yet such resources remain limite…

cs.CV2025

FrogDogNet: Fourier frequency Retained visual prompt Output Guidance for Domain Generalization of CLIP in Remote Sensing

Hariseetharam Gunduboina, Muhammad Haris Khan, Biplab Banerjee

In recent years, large-scale vision-language models (VLMs) like CLIP have gained attention for their zero-shot inference using instructional text prompts. While these models excel…

cs.CV2025

OSLoPrompt: Bridging Low-Supervision Challenges and Open-Set Domain Generalization in CLIP

Mohamad Hassan N C, Divyam Gupta, Mainak Singha +4

We introduce Low-Shot Open-Set Domain Generalization (LSOSDG), a novel paradigm unifying low-shot learning with open-set domain generalization (ODG). While prompt-based methods usi…