21 citations · 34 across the 35 of their papers we have counts for
6 papers · 1 filter
RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using Weighted and Majority Voted Fine-Tuned Transformers
Pratinav Seth, Rashi Goel, Komal Mathur +1
This paper describes our approach to submissions made at Shared Task 2 at BLP Workshop - Sentiment Analysis of Bangla Social Media Posts. Sentiment Analysis is an action research a…
ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation
Aditya Kasliwal, Sankarshanaa Sagaram, Laven Srivastava +2
Semantic segmentation of brain tumours is a fundamental task in medical image analysis that can help clinicians in diagnosing the patient and tracking the progression of any malign…
CoReFusion: Contrastive Regularized Fusion for Guided Thermal Super-Resolution
Aditya Kasliwal, Pratinav Seth, Sriya Rallabandi +1
Thermal imaging has numerous advantages over regular visible-range imaging since it performs well in low-light circumstances. Super-Resolution approaches can broaden their usefulne…
SSS at SemEval-2023 Task 10: Explainable Detection of Online Sexism using Majority Voted Fine-Tuned Transformers
Sriya Rallabandi, Sanchit Singhal, Pratinav Seth
This paper describes our submission to Task 10 at SemEval 2023-Explainable Detection of Online Sexism (EDOS), divided into three subtasks. The recent rise in social media platforms…
UATTA-EB: Uncertainty-Aware Test-Time Augmented Ensemble of BERTs for Classifying Common Mental Illnesses on Social Media Posts
Pratinav Seth, Mihir Agarwal
Given the current state of the world, because of existing situations around the world, millions of people suffering from mental illnesses feel isolated and unable to receive help i…
Analyzing Effects of Fake Training Data on the Performance of Deep Learning Systems
Pratinav Seth, Akshat Bhandari, Kumud Lakara
Deep learning models frequently suffer from various problems such as class imbalance and lack of robustness to distribution shift. It is often difficult to find data suitable for t…