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pro vyhledávání: '"Sharma, Anantha"'
Autor:
Sharma, Anantha, Deshmukh, Ajinkya
With the increasing demand for data sharing across platforms and organizations, ensuring the privacy and security of sensitive information has become a critical challenge. This paper introduces "TableGuard". An innovative approach to data obfuscation
Externí odkaz:
http://arxiv.org/abs/2408.07045
Autor:
Nikroo, Fatemeh Rezapoor, Deshmukh, Ajinkya, Sharma, Anantha, Tam, Adrian, Kumar, Kaarthik, Norris, Cleo, Dangi, Aditya
In this study, we evaluate the performance of multiple state-of-the-art SRGAN (Super Resolution Generative Adversarial Network) models, ESRGAN, Real-ESRGAN and EDSR, on a benchmark dataset of real-world images which undergo degradation using a pipeli
Externí odkaz:
http://arxiv.org/abs/2307.09456
Protecting sensitive information is crucial in today's world of Large Language Models (LLMs) and data-driven services. One common method used to preserve privacy is by using data perturbation techniques to reduce overreaching utility of (sensitive) P
Externí odkaz:
http://arxiv.org/abs/2305.09550
The use of machine learning algorithms to model user behavior and drive business decisions has become increasingly commonplace, specifically providing intelligent recommendations to automated decision making. This has led to an increase in the use of
Externí odkaz:
http://arxiv.org/abs/2106.15343
Computer aided Tabular Data Extraction has always been a very challenging and error prone task because it demands both Spectral and Spatial Sanity of data. In this paper we discuss an approach for Tabular Data Extraction in the realm of document comp
Externí odkaz:
http://arxiv.org/abs/2105.09137
This paper discusses the effectiveness of various text processing techniques, their combinations, and encodings to achieve a reduction of complexity and size in a given text corpus. The simplified text corpus is sent to BERT (or similar transformer b
Externí odkaz:
http://arxiv.org/abs/2009.12695
Autor:
Banthia, Saumya, Sharma, Anantha
This document describes a possible approach that can be used to check the relevance of a summary / definition of an entity with respect to its name. This classifier focuses on the relevancy of an entity's name to its summary / definition, in other wo
Externí odkaz:
http://arxiv.org/abs/2009.04953
Publikováno v:
Current Science, 2006 Mar . 90(6), 804-811.
Externí odkaz:
https://www.jstor.org/stable/24089192
Autor:
Sharma, Anantha Krishna1, Singh, Mewa1 msingh@psychology.uni-mysore.ac.in, Kaumanns, Werner2, Krebs, Ellen2, Singh, Mridula1, Kumar, M. Ananda1, Kumara, H. N.1
Publikováno v:
International Journal of Primatology. Oct2006, Vol. 27 Issue 5, p1429-1439. 11p. 2 Charts, 4 Graphs.
Publikováno v:
EAI Endorsed Transactions on Cloud Systems; 2019, Vol. 5 Issue 14, p1-5, 5p