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researcher

N. Dhar

4 papers hereh-index 241.9k citations235 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • cond-mat.mtrl-sci1
  • cs.CV1
same name
  • N. Dhar — 5 papers, h 11
  • N. Dhar — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20032019
most citedElectronic Structure of Te and As Covered Si(211)

12 citations · 14 across the 3 of their papers we have counts for

collaborators

4 papers

eess.IV2019★ 2 cited

GlidarCo: gait recognition by 3D skeleton estimation and biometric feature correction of flash lidar data

Nasrin Sadeghzadehyazdi, Tamal Batabyal, Nibir K. Dhar +3

Gait recognition using noninvasively acquired data has been attracting an increasing interest in the last decade. Among various modalities of data sources, it is experimentally fou…

eess.IV2019

Glidar3DJ: A View-Invariant gait identification via flash lidar data correction

Nasrin Sadeghzadehyazdi, Tamal Batabyal, A. Glandon +4

Gait recognition is a leading remote-based identification method, suitable for real-world surveillance and medical applications. Model-based gait recognition methods have been part…

cs.CV2018

Reservoir Computing based Neural Image Filters

Samiran Ganguly, Yunfei Gu, Yunkun Xie +3

Clean images are an important requirement for machine vision systems to recognize visual features correctly. However, the environment, optics, electronics of the physical imaging s…

cond-mat.mtrl-sci2003★ 12 cited

Electronic Structure of Te and As Covered Si(211)

Prasenjit Sen, Inder P. Batra, S. Sivananthan +3

Electronic and atomic structures of the clean, and As and Te covered Si(211) surface are studied using pseudopotential density functional method. The clean surface is found to have…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.