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V. Devarajan

3 papers hereh-index 12613 citations82 works total

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

author position
  • middle author1
  • last author2

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

fields
  • cs.LG2
  • cs.CV1

identity via Semantic Scholar / OpenAlex

activity
20192021
most citedLapTool-Net: A Contextual Detector of Surgical Tools in Laparoscopic Videos Based on Recurrent Convolutional Neural Networks

8 citations · 8 across the 2 of their papers we have counts for

collaborators

3 papers

cs.LG2021

Generation and Analysis of Feature-Dependent Pseudo Noise for Training Deep Neural Networks

Sree Ram Kamabattula, Kumudha Musini, Babak Namazi +2

Training Deep neural networks (DNNs) on noisy labeled datasets is a challenging problem, because learning on mislabeled examples deteriorates the performance of the network. As the…

cs.LG2020

Identifying Training Stop Point with Noisy Labeled Data

Sree Ram Kamabattula, Venkat Devarajan, Babak Namazi +1

Training deep neural networks (DNNs) with noisy labels is a challenging problem due to over-parameterization. DNNs tend to essentially fit on clean samples at a higher rate in the…

cs.CV2019★ 8 cited

LapTool-Net: A Contextual Detector of Surgical Tools in Laparoscopic Videos Based on Recurrent Convolutional Neural Networks

Babak Namazi, Ganesh Sankaranarayanan, Venkat Devarajan

We propose a new multilabel classifier, called LapTool-Net to detect the presence of surgical tools in each frame of a laparoscopic video. The novelty of LapTool-Net is the exploit…

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