125 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Indian Institute of Technology GuwahatiIN28 papers
- Indian Institute of Technology DelhiIN2 papers
- Indian Statistical InstituteIN2 papers
- National Sun Yat-sen UniversityTW2 papers
- Aalborg UniversityDK1 paper
- Amazon (United States)US1 paper
- Australian National UniversityAU1 paper
- Birla Institute of Technology and Science - Hyderabad CampusIN1 paper
- Bowling Green State UniversityUS1 paper
- Brookhaven National LaboratoryUS1 paper
- Budker Institute of Nuclear PhysicsRU1 paper
- Cellworks Research (India)IN1 paper
5 papers · 1 filter
Semi-equivelar toroidal maps and their k-edge covers
Arnab Kundu, Dipendu Maity
If the face\mbox{-}cycles at all the vertices in a map are of same type then the map is called semi\mbox{-}equivelar. A tiling is edge-homogeneous if any two edges with vertices of…
Search for the in at near 10.6 GeV at Belle
Belle Collaboration, S. Jia, C. P. Shen +198
For the first time we search for the in at = 10.52, 10.58, and 10.867 GeV with data samples of 89.5 fb, 711 fb, and 121…
Statistical inference for Gumbel Type-II distribution under simple step-stress life test using Type-II censoring
Subhankar Dutta, Farha Sultana, Suchandan Kayal
In this paper, we focus on the parametric inference based on the Tampered Random Variable (TRV) model for simple step-stress life testing (SSLT) using Type-II censored data. The ba…
Multiple Antenna Selection and Successive Signal Detection for SM-based IRS-aided Communication
Hasan Albinsaid, Keshav Singh, Ankur Bansal +3
Intelligent reflecting surface (IRS) is being considered as a prospective candidate for next-generation wireless communication due to its ability to significantly improve coverage…
Fixed-MAML for Few Shot Classification in Multilingual Speech Emotion Recognition
Anugunj Naman, Chetan Sinha, Liliana Mancini
In this paper, we analyze the feasibility of applying few-shot learning to speech emotion recognition task (SER). The current speech emotion recognition models work exceptionally w…