H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 45 Citations 8,253 245 World Ranking 3546 National Ranking 160

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His main research concerns Artificial intelligence, Computer vision, Object detection, Video tracking and Sensor fusion. In his research on the topic of Artificial intelligence, Probabilistic logic and Mixture model is strongly related with Machine learning. His Computer vision research incorporates themes from Kalman filter and Laser scanning.

The Object detection study combines topics in areas such as Segmentation, Data mining, Feature, Lidar and Robustness. Klaus Dietmayer has included themes like Covariance function and Vehicle tracking system in his Video tracking study. His Sensor fusion research is multidisciplinary, incorporating elements of Signal and High-definition video.

His most cited work include:

  • Three Decades of Driver Assistance Systems: Review and Future Perspectives (427 citations)
  • The Labeled Multi-Bernoulli Filter (365 citations)
  • Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods (252 citations)

What are the main themes of his work throughout his whole career to date?

Artificial intelligence, Computer vision, Object detection, Sensor fusion and Object are his primary areas of study. His work carried out in the field of Artificial intelligence brings together such families of science as Radar and Pattern recognition. The study incorporates disciplines such as Lidar, Advanced driver assistance systems, Radar engineering details and Laser scanning in addition to Computer vision.

In his work, Machine learning is strongly intertwined with Probabilistic logic, which is a subfield of Object detection. Klaus Dietmayer focuses mostly in the field of Sensor fusion, narrowing it down to topics relating to Real-time computing and, in certain cases, Simulation. As part of the same scientific family, Klaus Dietmayer usually focuses on Tracking, concentrating on Filter and intersecting with Algorithm.

He most often published in these fields:

  • Artificial intelligence (58.18%)
  • Computer vision (43.90%)
  • Object detection (18.18%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (58.18%)
  • Computer vision (43.90%)
  • Object detection (18.18%)

In recent papers he was focusing on the following fields of study:

Klaus Dietmayer mainly investigates Artificial intelligence, Computer vision, Object detection, Lidar and Object. His Artificial intelligence course of study focuses on Machine learning and Kalman filter. Advanced driver assistance systems is closely connected to Radar in his research, which is encompassed under the umbrella topic of Computer vision.

The various areas that Klaus Dietmayer examines in his Object detection study include Point cloud, Data mining, Probabilistic logic, Convolutional neural network and Sensor fusion. Klaus Dietmayer combines subjects such as Artificial neural network, Odometry and RGB color model with his study of Lidar. His studies deal with areas such as Occupancy grid mapping, Representation, Digital mapping and Task as well as Object.

Between 2017 and 2021, his most popular works were:

  • Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges (148 citations)
  • Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection (108 citations)
  • Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep Learning Approach with Fully Automatic Labeling (71 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Electrical engineering

The scientist’s investigation covers issues in Artificial intelligence, Object detection, Computer vision, Lidar and Sensor fusion. As a part of the same scientific study, he usually deals with the Artificial intelligence, concentrating on Pattern recognition and frequently concerns with Recurrent neural network. His Object detection study combines topics from a wide range of disciplines, such as Artificial neural network, Detector and Exploit.

In Computer vision, he works on issues like Radar, which are connected to Entropy. His Lidar research integrates issues from Sampling, Data mining and Backscatter. The concepts of his Occupancy grid mapping study are interwoven with issues in Video tracking, Representation, Convolutional neural network and Vehicle dynamics.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Three Decades of Driver Assistance Systems: Review and Future Perspectives

Klaus Bengler;Klaus Dietmayer;Berthold Farber;Markus Maurer.
ieee intelligent transportation systems (2014)

726 Citations

The Labeled Multi-Bernoulli Filter

Stephan Reuter;Ba-Tuong Vo;Ba-Ngu Vo;Klaus Dietmayer.
IEEE Transactions on Signal Processing (2014)

543 Citations

State-of-health monitoring of lithium-ion batteries in electric vehicles by on-board internal resistance estimation

Juergen Remmlinger;Michael Buchholz;Markus Meiler;Peter Bernreuter.
Journal of Power Sources (2011)

355 Citations

Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods

Adnan Nuhic;Tarik Terzimehic;Thomas Soczka-Guth;Michael Buchholz.
Journal of Power Sources (2013)

354 Citations

Pedestrian recognition in urban traffic using a vehicle based multilayer laserscanner

K.Ch. Fuerstenberg;K.C.J. Dietmayer;V. Willhoeft.
Information Visualization (2002)

241 Citations

Probabilistic trajectory prediction with Gaussian mixture models

Jurgen Wiest;Matthias Hoffken;Ulrich Kresel;Klaus Dietmayer.
ieee intelligent vehicles symposium (2012)

233 Citations

Situation Assessment of an Autonomous Emergency Brake for Arbitrary Vehicle-to-Vehicle Collision Scenarios

N. Kaempchen;B. Schiele;K. Dietmayer.
IEEE Transactions on Intelligent Transportation Systems (2009)

208 Citations

Model-Based Object Classification and Object tracking in Traffic Scenes from range-Images

K. C. Dietmayer.
IV2001 (2001)

164 Citations

Continuous Driver Intention Recognition with Hidden Markov Models

H. Berndt;J. Emmert;K. Dietmayer.
international conference on intelligent transportation systems (2008)

160 Citations

Lane detection and street type classification using laser range images

J. Sparbert;K. Dietmayer;D. Streller.
ieee intelligent transportation systems (2001)

155 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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