Zobrazeno 1 - 10
of 596
pro vyhledávání: '"Banerjee Subhashis"'
Publikováno v:
2024 IEEE 37th Computer Security Foundations Symposium (CSF)
While existing literature on electronic voting has extensively addressed verifiability of voting protocols, the vulnerability of electoral rolls in large public elections remains a critical concern. To ensure integrity of electoral rolls, the current
Externí odkaz:
http://arxiv.org/abs/2402.11582
Autor:
Agrawal, Prashant, Nakarmi, Abhinav, Jhawar, Mahavir Prasad, Sharma, Subodh, Banerjee, Subhashis
Publikováno v:
Proceedings on Privacy Enhancing Technologies 2024(2)
We introduce the notion of \emph{traceable mixnets}. In a traditional mixnet, multiple mix-servers jointly permute and decrypt a list of ciphertexts to produce a list of plaintexts, along with a proof of correctness, such that the association between
Externí odkaz:
http://arxiv.org/abs/2305.08138
Autor:
Baby, Britty, Thapar, Daksh, Chasmai, Mustafa, Banerjee, Tamajit, Dargan, Kunal, Suri, Ashish, Banerjee, Subhashis, Arora, Chetan
Minimally invasive surgeries and related applications demand surgical tool classification and segmentation at the instance level. Surgical tools are similar in appearance and are long, thin, and handled at an angle. The fine-tuning of state-of-the-ar
Externí odkaz:
http://arxiv.org/abs/2211.16200
Autor:
Agrawal, Prashant, Nakarmi, Abhinav, Jhanwar, Mahabir Prasad, Sharma, Subodh, Banerjee, Subhashis
We study the problem of simultaneously addressing both ballot stuffing and participation privacy for pollsite voting systems. Ballot stuffing is the attack where fake ballots (not cast by any eligible voter) are inserted into the system. Participatio
Externí odkaz:
http://arxiv.org/abs/2210.14833
Autor:
Daoud, Adel, Jordan, Felipe, Sharma, Makkunda, Johansson, Fredrik, Dubhashi, Devdatt, Paul, Sourabh, Banerjee, Subhashis
In this paper, we use deep learning to estimate living conditions in India. We use both census and surveys to train the models. Our procedure achieves comparable results to those found in the literature, but for a wide range of outcomes.
Externí odkaz:
http://arxiv.org/abs/2202.00109
Autor:
Mehta, Raghav, Filos, Angelos, Baid, Ujjwal, Sako, Chiharu, McKinley, Richard, Rebsamen, Michael, Datwyler, Katrin, Meier, Raphael, Radojewski, Piotr, Murugesan, Gowtham Krishnan, Nalawade, Sahil, Ganesh, Chandan, Wagner, Ben, Yu, Fang F., Fei, Baowei, Madhuranthakam, Ananth J., Maldjian, Joseph A., Daza, Laura, Gomez, Catalina, Arbelaez, Pablo, Dai, Chengliang, Wang, Shuo, Reynaud, Hadrien, Mo, Yuan-han, Angelini, Elsa, Guo, Yike, Bai, Wenjia, Banerjee, Subhashis, Pei, Lin-min, AK, Murat, Rosas-Gonzalez, Sarahi, Zemmoura, Ilyess, Tauber, Clovis, Vu, Minh H., Nyholm, Tufve, Lofstedt, Tommy, Ballestar, Laura Mora, Vilaplana, Veronica, McHugh, Hugh, Talou, Gonzalo Maso, Wang, Alan, Patel, Jay, Chang, Ken, Hoebel, Katharina, Gidwani, Mishka, Arun, Nishanth, Gupta, Sharut, Aggarwal, Mehak, Singh, Praveer, Gerstner, Elizabeth R., Kalpathy-Cramer, Jayashree, Boutry, Nicolas, Huard, Alexis, Vidyaratne, Lasitha, Rahman, Md Monibor, Iftekharuddin, Khan M., Chazalon, Joseph, Puybareau, Elodie, Tochon, Guillaume, Ma, Jun, Cabezas, Mariano, Llado, Xavier, Oliver, Arnau, Valencia, Liliana, Valverde, Sergi, Amian, Mehdi, Soltaninejad, Mohammadreza, Myronenko, Andriy, Hatamizadeh, Ali, Feng, Xue, Dou, Quan, Tustison, Nicholas, Meyer, Craig, Shah, Nisarg A., Talbar, Sanjay, Weber, Marc-Andre, Mahajan, Abhishek, Jakab, Andras, Wiest, Roland, Fathallah-Shaykh, Hassan M., Nazeri, Arash, Milchenko1, Mikhail, Marcus, Daniel, Kotrotsou, Aikaterini, Colen, Rivka, Freymann, John, Kirby, Justin, Davatzikos, Christos, Menze, Bjoern, Bakas, Spyridon, Gal, Yarin, Arbel, Tal
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 1 (2022)
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e
Externí odkaz:
http://arxiv.org/abs/2112.10074
Autor:
Banerjee, Subhashis1 (AUTHOR) subhashis.banerjee@it.uu.se, Nysjö, Fredrik1 (AUTHOR), Toumpanakis, Dimitrios2 (AUTHOR), Dhara, Ashis Kumar3 (AUTHOR), Wikström, Johan2 (AUTHOR), Strand, Robin1 (AUTHOR) robin.strand@it.uu.se
Publikováno v:
Scientific Reports. 4/22/2024, Vol. 14 Issue 1, p1-12. 12p.
Prediction of Overall Survival (OS) of brain cancer patients from multi-modal MRI is a challenging field of research. Most of the existing literature on survival prediction is based on Radiomic features, which does not consider either non-biological
Externí odkaz:
http://arxiv.org/abs/2109.02785
Autor:
Blauvelt, Andrew, Rich, Phoebe, Sofen, Howard, Strober, Bruce, Merola, Joseph F., Lebwohl, Mark, Morita, Akimichi, Szepietowski, Jacek C., Lambert, Jo, Hippeli, Lauren, Colston, Elizabeth, Balagula, Eugene, Banerjee, Subhashis, Thaçi, Diamant
Publikováno v:
In Journal of the American Academy of Dermatology April 2024 90(4):775-782
Deep Neural Networks (DNNs) are often criticized for being susceptible to adversarial attacks. Most successful defense strategies adopt adversarial training or random input transformations that typically require retraining or fine-tuning the model to
Externí odkaz:
http://arxiv.org/abs/2006.10679