Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Tashvik Dhamija"'
Autor:
Indu Joshi, Tashvik Dhamija, Rohit Kumar, Antitza Dantcheva, Sumantra Dutta Roy, Prem Kumar Kalra
Publikováno v:
IEEE Sensors Letters
IEEE Sensors Letters, 2022, 6 (8), ⟨10.1109/LSENS.2022.3193924⟩
IEEE Sensors Letters, 2022, 6 (8), ⟨10.1109/LSENS.2022.3193924⟩
International audience; Performance of state-of-the-art fingerprint denoising model on poor quality fingerprints degrades due to crossdomain shift observed between training and testing domains. To address this limitation, we present a cross-domain co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e108b7ed5a69e7974451f685824fc617
https://hal.science/hal-03966789/document
https://hal.science/hal-03966789/document
Publikováno v:
Applied intelligence (Dordrecht, Netherlands). 53(1)
Recent decades have witnessed rapid development in the field of medical image segmentation. Deep learning-based fully convolution neural networks have played a significant role in the development of automated medical image segmentation models. Though
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a41f881ba1946e63c34989035e136456
https://pubmed.ncbi.nlm.nih.gov/35498554
https://pubmed.ncbi.nlm.nih.gov/35498554
Autor:
Anunay Gupta, Shreyansh Gupta, Aakansha Gupta, Anjum, Tashvik Dhamija, Priyansh Kedia, Varang Rai, Shelly Sachdeva, Rahul Katarya
Publikováno v:
2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS).
With over a hundred million cases worldwide and thousands coming daily, the outbreak of COVID-19 has seriously affected many countries' healthcare and economic situations. A precise and efficient model for predicting new COVID-19 cases and the pandem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea91c9d3e1078a87f812248a20aea7ac
https://doi.org/10.1109/icaccs51430.2021.9441966
https://doi.org/10.1109/icaccs51430.2021.9441966
Publikováno v:
Advances in Mechanical Engineering ISBN: 9789811609411
In the day and age of social media, users have become prone to online hate speech. Several attempts have been made to classify hate speech using machine learning, but the state-of-the-art models are not robust enough for practical applications. This
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d9e7afe4b6959fa5f063f8b2db2e468
https://doi.org/10.1007/978-981-16-0942-8_48
https://doi.org/10.1007/978-981-16-0942-8_48