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M. Schukat

4 papers hereh-index 201.4k citations74 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
  • cs.LG2
  • cs.CV1
  • eess.IV1

identity via Semantic Scholar / OpenAlex

activity
20172020
most citedTraffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning

2 citations · 2 across the 1 of their papers we have counts for

collaborators

4 papers

cs.CV2020

Methodology for Building Synthetic Datasets with Virtual Humans

Shubhajit Basak, Hossein Javidnia, Faisal Khan +2

Recent advances in deep learning methods have increased the performance of face detection and recognition systems. The accuracy of these models relies on the range of variation pro…

eess.IV2020

High-Accuracy Facial Depth Models derived from 3D Synthetic Data

Faisal Khan, Shubhajit Basak, Hossein Javidnia +2

In this paper, we explore how synthetically generated 3D face models can be used to construct a high accuracy ground truth for depth. This allows us to train the Convolutional Neur…

cs.LG2018

Deep Reinforcement Learning: An Overview

Seyed Sajad Mousavi, Michael Schukat, Enda Howley

In recent years, a specific machine learning method called deep learning has gained huge attraction, as it has obtained astonishing results in broad applications such as pattern re…

cs.LG2017★ 2 cited

Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning

Seyed Sajad Mousavi, Michael Schukat, Enda Howley

Recent advances in combining deep neural network architectures with reinforcement learning techniques have shown promising potential results in solving complex control problems wit…

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