20 citations · 28 across the 3 of their papers we have counts for
3 papers
Identifying Semantically Difficult Samples to Improve Text Classification
Shashank Mujumdar, Stuti Mehta, Hima Patel +1
In this paper, we investigate the effect of addressing difficult samples from a given text dataset on the downstream text classification task. We define difficult samples as being…
Towards a Multi-modal, Multi-task Learning based Pre-training Framework for Document Representation Learning
Subhojeet Pramanik, Shashank Mujumdar, Hima Patel
Recent approaches in literature have exploited the multi-modal information in documents (text, layout, image) to serve specific downstream document tasks. However, they are limited…
Small, Sparse, but Substantial: Techniques for Segmenting Small Agricultural Fields Using Sparse Ground Data
Smit Marvaniya, Umamaheswari Devi, Jagabondhu Hazra +2
The recent thrust on digital agriculture (DA) has renewed significant research interest in the automated delineation of agricultural fields. Most prior work addressing this problem…