VLSM-Adapter: Finetuning Vision-Language Segmentation Efficiently with Lightweight Blocks

no code implementations • 10 May 2024 • Manish Dhakal, Rabin Adhikari, Safal Thapaliya, Bishesh Khanal

Foundation Vision-Language Models (VLMs) trained using large-scale open-domain images and text pairs have recently been adapted to develop Vision-Language Segmentation Models (VLSMs) that allow providing text prompts during inference to guide image segmentation.

Synthetic Boost: Leveraging Synthetic Data for Enhanced Vision-Language Segmentation in Echocardiography

1 code implementation • 22 Sep 2023 • Rabin Adhikari, Manish Dhakal, Safal Thapaliya, Kanchan Poudel, Prasiddha Bhandari, Bishesh Khanal

However, the lack of readily available data in echocardiography hampers the training of VLSMs.

Segmentation Vision-Language Segmentation

Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Models

1 code implementation • 15 Aug 2023 • Kanchan Poudel, Manish Dhakal, Prasiddha Bhandari, Rabin Adhikari, Safal Thapaliya, Bishesh Khanal

Medical image segmentation with deep learning is an important and widely studied topic because segmentation enables quantifying target structure size and shape that can help in disease diagnosis, prognosis, surgery planning, and understanding.

Image Segmentation Medical Image Segmentation +3

COVID-19-related Nepali Tweets Classification in a Low Resource Setting

1 code implementation • SMM4H (COLING) 2022 • Rabin Adhikari, Safal Thapaliya, Nirajan Basnet, Samip Poudel, Aman Shakya, Bishesh Khanal

Billions of people across the globe have been using social media platforms in their local languages to voice their opinions about the various topics related to the COVID-19 pandemic.