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Muhammad Annas Shaikh

3 papers hereh-index 00 citations3 works total

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author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3

identity via Semantic Scholar / OpenAlex

works on
gastrointestinal endoscopy 1model grounding 1multitask learning 1vision-language models 1visual question answering 1

From the 1 of 3 linked papers with an AI index.

collaborators

3 papers

cs.CV2026

Towards Grounded GI Endoscopy VQA via Multi-Task Learning on Small VLMs

Itbaan Safwan, Ramail Khan, Muhammad Annas Shaikh +1

The paper introduces a multi‑task fine‑tuning approach for small vision‑language models to improve visual question answering on GI endoscopy images, adding grounding and descriptio…

cs.CV2025

Multi-Task Learning for Visually Grounded Reasoning in Gastrointestinal VQA

Itbaan Safwan, Muhammad Annas Shaikh, Muhammad Haaris +2

We present a multi-task framework for the MediaEval Medico 2025 challenge, leveraging a LoRA-tuned Florence-2 model for simultaneous visual question answering (VQA), explanation ge…

cs.CV2025

Comparative Study of CNN Architectures for Binary Classification of Horses and Motorcycles in the VOC 2008 Dataset

Muhammad Annas Shaikh, Hamza Zaman, Arbaz Asif

This paper presents a comprehensive evaluation of nine convolutional neural network architectures for binary classification of horses and motorcycles in the VOC 2008 dataset. We ad…

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