Zobrazeno 1 - 10
of 2 633
pro vyhledávání: '"P. Yuvaraj"'
Autor:
Narayanam Srikanth, Adarsh Kumar, Bhogavalli Chandrasekhararao, Richa Singhal, Babita Yadav, Shruti Khanduri, Sophia Jameela, Amit Kumar Rai, Arunabh Tripathi, Rakesh Rana, Azeem Ahmad, Bhagwan Sahai Sharma, Ankit Jaiswal, Rajesh Kotecha, State Level Collaborators, Tanuja Nesari, Mahesh Vyas, Umesh Tagade, Anup Thakar, Nilesh Bhatt, Kalpesh Dattani, Sagar Bhinde, Sanjeev Sharma, Pawan Kumar Godatwar, Nisha Ojha, H.M.L. Meena, Harish Bhakuni, Pradeep Kumar Goswami, Bishnu Choudhury, K Nishanth, AJV Sai Prasad, Sujata Dhoke, K Midhuna Mohan, Savita Gopod, Arvind Kumar, Ekta Dogra, G.K. Bora, K S Pravin, Pravin Masarom Radheshyam, P.L. Bharati, Jeuti Rani Das, Vimal Tewari, Deepika Tewari, Ritika Mishra, Kuldeep, D.S. Rotwar, Anil Ahvad, Sumed Paikrao, Amit Madan, Nandini Jadhav, Vikas Nariyal, Kavita Vyas, Anubha Chandla, Vineeta Negi, Chris Antony, Vipin Sharma, Poonam Mohod, Subhash Sharma, Meenakshi Suri, Aaditya Shah, G.V. Ramana, C Tejaswini, Raghavendra, S.K. Giri, Shashidhar Doddamani, M.N Shubhashree, Srinibash Sahoo, K.M. Pratap Shankar, Parvathy.G. Nair, Devi R Nair, V. Krishna Kumar, P.P. Pradeep Kumar, E Remya, A P Karthika, T.P Sinimol, P P Meghna, Praveen Balakrishnan, Emy.S. Surendran, Varsha Sumedhan, Amit Kumar, S.B. Singh, Neelam Singh, Anil Mangal, Deepa Sharma, Laxman Bhurke, Dattatray Dighe, Kuldeep Choudhary, Saylee Deshmukh, Sneha Marlewar, Shyam Kale, U.R. Shekhar Namboori, Savita Sharma, Priya Thakre, Prashant Shinde, Balaji Potbare, Deepak Rahangdale, Gwachung Magh, G.C. Bhuyan, P. Panda, K.K. Ratha, Krishna Rao, S Indu, A.K. Panda, Banamali Das, Susmita Ota, Rinku Tomar, Harbans Singh, Sandeep Baheti, Sanjeev Kumar, S Mahesh, Sangeeta Sangvikar, S.K. Vedi, Swati Sharma, V.B. Kumawat, Suhash Choudhary, Monika Kumari, P P Indu, Rahul D. Ghuse, Shriprakash, Shrawan Kumar Sahu, Ashok Kumar Sinha, P. Srinivas, K. Prameela Devi, S Asha, Sojeetra Niral, Karisma Singh, Kamble Pallavi, Ravi Ranjan Singh, Anjali B Prasad, Mayur Surana, Sanjay Kumar Singh, Harit Kumari, A.K. Srivastava, Tarun Kumar, Deepshikha Arya, D.S. Sahu, Tushar Kanti Mondal, L.D. Barik, Suparna Saha, Ranjita Ekka, Shakti Bhushan, Achintya Mitra, Saroj Kumar Debnath, Debajyoti Das, M Akashlal, A Abhayadev, Hemant Gupta, Ajay P Yadav, Asim Ali Khan, Munawar H Kazmi, Minhaj, Rahat Raza, Md.Nafees Khan, Md. Ishtiyaq Alam, Haseeb Alam Lari, N. Zaheer Ahmed, Hakimuddin Khan, Younis Iftikhar, Seema Akbar, Sheeren Afza, Mohammad Fazil, Ashok Kumar, Mohd Tarique, Amir Faisal Khan, Aijaz Ahmed, Anil Khurana, S. Karunakara Moorthi, Subhash Kaushik, Nitin Kumar Saklani, B. S. Rawat, Brunda Bezawada, Sunil Ramteke, A.K. Prusty, Liyi Karso, Amit Srivastav, Ratan Chandra Shil, Partha Pratim Pal, Lipipushpa Debata, G. Ravi Chandra Reddy, Sunil Prasad, Uttam Singh, Baidurjya Bhattacharjee, Santosh Kumar Tamang, Ravi kumar Sadarla, Pawan Sharma, Amulya Ratna Sahoo, Vibha, P Prasad, D. Karthikeyan, Raghvendra Rao, Surender Sandhu, Mohan Rao, HS Vadiraj, Ishwar V. Basavaraddi, Ishwar N Achary, K Satyalakshmi, Shivkesh, P. Yuvaraj Paul, Subhas Singh, Austin Jose, Robindra Teron, Imlikumba, Addul Wadud, Abdul Nasir Ansari, Tariq Nadeem Khan, Abdul Moheen, Tsewang Dolma, Tenzin Tenba, Anupam Srivastav, N. Ramakrishnan, Surendra Soni, Ram Shukla, Rohini Salve, M.N. Shaikh, Daxen Trivedi, Shital Bhagiya, Asha Patel, Anup Indoriya, Rachna Gandhi, Naresh Jain, Nirmal Chavada, Rahul Shingadiya, Nilesh Bhadraka, Nrupesh Gupta, Dilip Italiya, Piyush Shah, Maya Chaudhari, Sumit Patel, Bhavin Chaudhari, Mehul Parmar
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
BackgroundDuring the second wave of the COVID-19 pandemic in India, the Ministry of Ayush conducted a community study to provide therapeutic care to patients with asymptomatic, mild, and moderate COVID-19 in home isolation based on the empirical evid
Externí odkaz:
https://doaj.org/article/ae64239b77ac4a5f845b2816a95b8d66
In the domain of black-box model extraction, conventional methods reliant on soft labels or surrogate datasets struggle with scaling to high-dimensional input spaces and managing the complexity of an extensive array of interrelated classes. In this w
Externí odkaz:
http://arxiv.org/abs/2408.02140
The recent strides in artificial intelligence (AI) and machine learning (ML) have propelled the rise of TinyML, a paradigm enabling AI computations at the edge without dependence on cloud connections. While TinyML offers real-time data analysis and s
Externí odkaz:
http://arxiv.org/abs/2407.11599
Autor:
Chesetti, Yuvaraj, Pandey, Prashant
In this paper, we investigate the effectiveness of utilizing CDF-based learned indexes in indexed-nested loop joins for both sorted and unsorted data in external memory. Our experimental study seeks to determine whether the advantages of learned inde
Externí odkaz:
http://arxiv.org/abs/2407.00590
Large language models (LLMs) have revolutionized how we interact with machines. However, this technological advancement has been paralleled by the emergence of "Mallas," malicious services operating underground that exploit LLMs for nefarious purpose
Externí odkaz:
http://arxiv.org/abs/2406.00628
Nanocomposites comprising of high surface area adsorption materials and nanosized transition metals have emerged as a promising strategy for hydrogen storage application due to their inherent ability to store atomic and molecular forms of hydrogen by
Externí odkaz:
http://arxiv.org/abs/2405.17831
Emerging vulnerabilities in machine learning (ML) models due to adversarial attacks raise concerns about their reliability. Specifically, evasion attacks manipulate models by introducing precise perturbations to input data, causing erroneous predicti
Externí odkaz:
http://arxiv.org/abs/2404.15656
The rapid integration of Large Language Models (LLMs) across diverse sectors has marked a transformative era, showcasing remarkable capabilities in text generation and problem-solving tasks. However, this technological advancement is accompanied by s
Externí odkaz:
http://arxiv.org/abs/2403.13309
Autor:
Ismaeel, Ayad Ghany, Janardhanan, Krishnadas, Sankar, Manishankar, Natarajan, Yuvaraj, Mahmood, Sarmad Nozad, Alani, Sameer, Shather, Akram H.
Publikováno v:
sustainability 2023, 15, 14522
This paper examines the use of deep recurrent neural networks to classify traffic patterns in smart cities. We propose a novel approach to traffic pattern classification based on deep recurrent neural networks, which can effectively capture traffic p
Externí odkaz:
http://arxiv.org/abs/2401.13794
Autor:
Bhardwaj, Gauri, Govindarajulu, Yuvaraj, Narayanan, Sundaraparipurnan, Kulkarni, Pavan, Parmar, Manojkumar
Medical imaging has revolutionized disease diagnosis, yet the potential is hampered by limited access to diverse and privacy-conscious datasets. Open-source medical datasets, while valuable, suffer from data quality and clinical information dispariti
Externí odkaz:
http://arxiv.org/abs/2312.06979