Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Maji, Subhadip"'
Bangla (or Bengali) is the fifth most spoken language globally; yet, the state-of-the-art NLP in Bangla is lagging for even simple tasks such as lemmatization, POS tagging, etc. This is partly due to lack of a varied quality corpus. To alleviate this
Externí odkaz:
http://arxiv.org/abs/2307.05083
Detection of semantic data types is a very crucial task in data science for automated data cleaning, schema matching, data discovery, semantic data type normalization and sensitive data identification. Existing methods include regular expression-base
Externí odkaz:
http://arxiv.org/abs/2106.12871
Autor:
Basu, Indranil, Maji, Subhadip
Model interpretability is one of the most intriguing problems in most of the Machine Learning models, particularly for those that are mathematically sophisticated. Computing Shapley Values are arguably the best approach so far to find the importance
Externí odkaz:
http://arxiv.org/abs/2011.01661
Autor:
Chattopadhyay, Tanuka, Mondal, Sreerup, Paul, Suman, Maji, Subhadip, Chattopadhyay, Asis Kumar
The present work explores the origin of the formation of star clusters in our Galaxy and in Small Magellanic Cloud (SMC) through simulated H-R diagrams and compare those with observed star clusters. The simulation study produces synthetic H-R diagram
Externí odkaz:
http://arxiv.org/abs/2010.15381
Autor:
Maji, Subhadip, Appe, Anudeep Srivatsav, Bali, Raghav, Chikka, Veera Raghavendra, Chowdhury, Arijit Ghosh, Bhandaru, Vamsi M
Publikováno v:
2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)
The Managed Care system within Medicaid (US Healthcare) uses Request For Proposals (RFP) to award contracts for various healthcare and related services. RFP responses are very detailed documents (hundreds of pages) submitted by competing organisation
Externí odkaz:
http://arxiv.org/abs/2008.02347
Publikováno v:
Proceedings of the Canadian Conference on Artificial Intelligence 2021
Deep Learning based models are currently dominating most state-of-the-art solutions for disease prediction. Existing works employ RNNs along with multiple levels of attention mechanisms to provide interpretability. These deep learning models, with tr
Externí odkaz:
http://arxiv.org/abs/2007.13351
Publikováno v:
2021 IEEE Symposium Series on Computational Intelligence (SSCI)
Deep Neural Networks in NLP have enabled systems to learn complex non-linear relationships. One of the major bottlenecks towards being able to use DNNs for real world applications is their characterization as black boxes. To solve this problem, we in
Externí odkaz:
http://arxiv.org/abs/2007.16010
Autor:
Maji, Subhadip, Bose, Smarajit
Estimating and rectifying the orientation angle of any image is a pretty challenging task. Initial work used the hand engineering features for this purpose, where after the invention of deep learning using convolution-based neural network showed sign
Externí odkaz:
http://arxiv.org/abs/2007.06709
Autor:
Maji, Subhadip, Bose, Smarajit
Introduction of Convolutional Neural Networks has improved results on almost every image-based problem and Content-Based Image Retrieval is not an exception. But the CNN features, being rotation invariant, creates problems to build a rotation-invaria
Externí odkaz:
http://arxiv.org/abs/2006.13046
Autor:
Maji, Subhadip, Bose, Smarajit
Relevance Feedback in Content-Based Image Retrieval is a method where the feedback of the performance is being used to improve itself. Prior works use feature re-weighting and classification techniques as the Relevance Feedback methods. This paper sh
Externí odkaz:
http://arxiv.org/abs/2006.11821