Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Sarkar, Mrinmoy"'
Publikováno v:
2024, Bulletin de la Societe Royale des Sciences de Liege, 94
In this paper, we report the detection of amplitude modulation in a delta Scuti star HD118660. We found that the p-mode frequency at 24.3837 c/d varies periodically in amplitude with frequency 0.0558 c/d. However, all other modes are stable in both a
Externí odkaz:
http://arxiv.org/abs/2402.03403
Autor:
Uppal, Namita, Ganesh, Shashikiran, Joshi, Santosh, Sarkar, Mrinmoy, Prajapati, Prachi, Dileep, Athul
Dust is a ubiquitous component in our Galaxy. It accounts for only $1\%$ mass of the ISM but still is an essential part of the Galaxy. It affects our view of the Galaxy by obscuring the starlight at shorter wavelengths and re-emitting in longer wavel
Externí odkaz:
http://arxiv.org/abs/2311.09617
Autor:
Yan, Xuyang, Nazmi, Shabnam, Gebru, Biniam, Anwar, Mohd, Homaifar, Abdollah, Sarkar, Mrinmoy, Gupta, Kishor Datta
In this paper, we proposed a new clustering-based active learning framework, namely Active Learning using a Clustering-based Sampling (ALCS), to address the shortage of labeled data. ALCS employs a density-based clustering approach to explore the clu
Externí odkaz:
http://arxiv.org/abs/2207.02964
Autor:
Sarkar, Mrinmoy
In this project, a state-of-the-art deep convolution neural network (DCNN) is presented to segment seismic images for salt detection below the earth's surface. Detection of salt location is very important for starting mining. Hence, a seismic image i
Externí odkaz:
http://arxiv.org/abs/2203.13721
Standard Convolutional Neural Network (CNN) designs rarely focus on the importance of explicitly capturing diverse features to enhance the network's performance. Instead, most existing methods follow an indirect approach of increasing or tuning the n
Externí odkaz:
http://arxiv.org/abs/2111.13157
Feature selection methods are widely used to address the high computational overheads and curse of dimensionality in classifying high-dimensional data. Most conventional feature selection methods focus on handling homogeneous features, while real-wor
Externí odkaz:
http://arxiv.org/abs/2111.08169
In this paper, we developed a generalized simulation framework for the evaluation of electric vertical takeoff and landing vehicles (eVTOLs) in the context of Unmanned Aircraft Systems (UAS) Traffic Management (UTM) and under the concept of Urban Air
Externí odkaz:
http://arxiv.org/abs/2111.05413
The non-stationary nature of data streams strongly challenges traditional machine learning techniques. Although some solutions have been proposed to extend traditional machine learning techniques for handling data streams, these approaches either req
Externí odkaz:
http://arxiv.org/abs/2106.11823
Autor:
Murmu, Nensina, Sarkar, Mrinmoy, Dey, Sananda, Manna, Rahul, Roy, Shreya, Mondal, Tanushree, Halder, Soma, Bhattacharjee, Nandini, Dash, Sandeep K., Giri, Biplab
Publikováno v:
In Journal of Medicine, Surgery, and Public Health April 2024 2
Autor:
Chatterjee, Bilash, Sarkar, Mrinmoy, Bose, Subhankar, Alam, Md Tanjim, Chaudhary, Anis Ahmad, Dixit, Amit Kumar, Tripathi, Prem Prakash, Srivastava, Amit Kumar
Publikováno v:
In Seminars in Cell and Developmental Biology 15 February 2024 154 Part C:364-373