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researcher

B. Kumar

4 papers hereh-index 3984 citations4 works total

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

author position
  • middle author2
  • last author2

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

fields
  • cs.CV3
  • cs.CL1
same name
  • B. Kumar — 58 papers, h 17
  • B. Kumar — 47 papers, h 16
  • B. Kumar — 35 papers, h 15
  • B. Kumar — 28 papers, h 38
  • B. Kumar — 17 papers, h 8
  • B. Kumar — 17 papers, h 6

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
20182021
most citedDomain Adaptation for Semantic Segmentation via Class-Balanced Self-Training

48 citations · 82 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2021

SPaR.txt, a cheap Shallow Parsing approach for Regulatory texts

Ruben Kruiper, Ioannis Konstas, Alasdair Gray +3

Automated Compliance Checking (ACC) systems aim to semantically parse building regulations to a set of rules. However, semantic parsing is known to be hard and requires large amoun…

cs.CV2019★ 1 cited

Deep Classification Network for Monocular Depth Estimation

Azeez Oluwafemi, Yang Zou, B. V. K. Vijaya Kumar

Monocular Depth Estimation is usually treated as a supervised and regression problem when it actually is very similar to semantic segmentation task since they both are fundamentall…

cs.CV2019★ 33 cited

Confidence Regularized Self-Training

Yang Zou, Zhiding Yu, Xiaofeng Liu +2

Recent advances in domain adaptation show that deep self-training presents a powerful means for unsupervised domain adaptation. These methods often involve an iterative process of…

cs.CV2018★ 48 cited

Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training

Yang Zou, Zhiding Yu, B. V. K. Vijaya Kumar +1

Recent deep networks achieved state of the art performance on a variety of semantic segmentation tasks. Despite such progress, these models often face challenges in real world `wil…

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