no code implementations • 28 Nov 2023 • Soumya Banerjee, Debarshi Kumar Sanyal, Samiran Chattopadhyay, Plaban Kumar Bhowmick, Partha Pratim Das
Digital libraries often face the challenge of processing a large volume of diverse document types.
Document Image Classification Optical Character Recognition (OCR)
no code implementations • 27 Oct 2023 • Srijoni Majumdar, Soumen Paul, Debjyoti Paul, Ayan Bandyopadhyay, Samiran Chattopadhyay, Partha Pratim Das, Paul D Clough, Prasenjit Majumder
The Information Retrieval in Software Engineering (IRSE) track aims to develop solutions for automated evaluation of code comments in a machine learning framework based on human and large language model generated labels.
no code implementations • 12 Aug 2023 • Srijoni Majumdar, Partha Pratim Das
To address the issue of rising software maintenance cost due to program comprehension challenges, we propose SMARTKT (Smart Knowledge Transfer), a search framework, which extracts and integrates knowledge related to various aspects of an application in form of a semantic graph.
2 code implementations • 27 Mar 2023 • Suman Adhya, Avishek Lahiri, Debarshi Kumar Sanyal, Partha Pratim Das
Topic modeling has emerged as a dominant method for exploring large document collections.
1 code implementation • 14 Feb 2023 • Tohida Rehman, Debarshi Kumar Sanyal, Samiran Chattopadhyay, Plaban Kumar Bhowmick, Partha Pratim Das
On the new MixSub dataset, where only the abstract is the input, our proposed model (when trained on the whole training corpus without distinguishing between the subject categories) achieves ROUGE-1, ROUGE-2 and ROUGE-L F1-scores of 31. 78, 9. 76 and 29. 3, respectively, METEOR score of 24. 00, and BERTScore F1 of 85. 25.
1 code implementation • Extraction and Evaluation of Knowledge Entities from Scientific Documents 2021 • T Y S S Santosh, Prantika Chakraborty, Sudakshina Dutta, Debarshi Kumar Sanyal, Partha Pratim Das
Scientific articles contain various types of domain-specific entities and relations between them.
Ranked #3 on Joint Entity and Relation Extraction on SciERC
Joint Entity and Relation Extraction Joint Entity and Relation Extraction on Scientific Data +3
no code implementations • 8 Dec 2020 • Ananda Das, Partha Pratim Das
This segmentation information eases user efforts of searching, locating and browsing a topic inside a lecture video.
no code implementations • COLING 2020 • T.y.s.s Santosh, Debarshi Kumar Sanyal, Plaban Kumar Bhowmick, Partha Pratim Das
Keyphrases in a research paper succinctly capture the primary content of the paper and also assist in indexing the paper at a concept level.
1 code implementation • 9 Nov 2020 • Soumava Paul, Gurunath Reddy M, K Sreenivasa Rao, Partha Pratim Das
Singing Voice Detection (SVD) has been an active area of research in music information retrieval (MIR).
no code implementations • 7 Mar 2020 • Bijju Kranthi Veduruparthi, Jayanta Mukherjee, Partha Pratim Das, Moses Arunsingh, Raj Kumar Shrimali, Sriram Prasath, Soumendranath Ray, Sanjay Chatterjee
Weekly variation in TMG of a patient is computed from the image data and also estimated from a cell survivability model.
no code implementations • 7 Mar 2020 • Bijju Kranthi Veduruparthi, Jayanta Mukherjee, Partha Pratim Das, Mandira Saha, Sanjoy Chatterjee, Raj Kumar Shrimali, Soumendranath Ray, Sriram Prasath
The mean Jacobian of these regions $\mu_U$, $\mu_G$ and $\mu_R$ are statistically compared and a response assessment model is proposed.
no code implementations • 24 Sep 2019 • Tanwi Mallick, Partha Pratim Das, Arun Kumar Majumdar
To develop an application for dance, three aspects of dance analysis need to be addressed: 1) Segmentation of the dance video to find the representative action elements, 2) Matching or recognition of the detected action elements, and 3) Recognition of the dance sequences formed by combining a number of action elements under certain rules.
no code implementations • 11 Nov 2018 • K. Sai Ram, Jayanta Mukherjee, Amit Patra, Partha Pratim Das
We report accuracies up to $85. 6\%$ ( $94. 75\%$ ) on scenarios with 13 ( 4 ) classes of CIFAR100, using a pre-trained VGG-16 network on the full data set.