H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 49 Citations 11,439 159 World Ranking 3048 National Ranking 38

Research.com Recognitions

Awards & Achievements

2009 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Antonio M. Lopez mainly focuses on Artificial intelligence, Computer vision, Pedestrian detection, Object detection and Machine learning. His Artificial intelligence research incorporates elements of Vehicle dynamics and Pattern recognition. In his work, Minification, Matching, Contrast, Image segmentation and Segmentation is strongly intertwined with Object, which is a subfield of Pattern recognition.

Many of his research projects under Computer vision are closely connected to Road surface with Road surface, tying the diverse disciplines of science together. The study incorporates disciplines such as Contextual image classification, Pixel, Pascal and Feature vector in addition to Object detection. Antonio M. Lopez studied Machine learning and Training set that intersect with Animation, Computer graphics, Dependency, Deep learning and Feature learning.

His most cited work include:

  • The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes (1055 citations)
  • Survey of Pedestrian Detection for Advanced Driver Assistance Systems (794 citations)
  • CARLA: An Open Urban Driving Simulator (766 citations)

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

His primary scientific interests are in Artificial intelligence, Computer vision, Machine learning, Pedestrian detection and Pattern recognition. All of his Artificial intelligence and Object detection, Segmentation, Classifier, Advanced driver assistance systems and Image segmentation investigations are sub-components of the entire Artificial intelligence study. His Object detection research is multidisciplinary, relying on both Contextual image classification, Feature extraction and Feature.

Within one scientific family, Antonio M. Lopez focuses on topics pertaining to Benchmark under Segmentation, and may sometimes address concerns connected to Artificial neural network. His Machine learning research includes elements of Task, Training set and Metaverse. His Pattern recognition study incorporates themes from Object and Representation.

He most often published in these fields:

  • Artificial intelligence (81.74%)
  • Computer vision (52.05%)
  • Machine learning (23.29%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (81.74%)
  • Machine learning (23.29%)
  • Computer vision (52.05%)

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

Antonio M. Lopez mostly deals with Artificial intelligence, Machine learning, Computer vision, Convolutional neural network and Pedestrian detection. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Pattern recognition. His Machine learning research is multidisciplinary, incorporating elements of Object, Metaverse and Task.

As a part of the same scientific study, Antonio M. Lopez usually deals with the Computer vision, concentrating on Computation and frequently concerns with Frame rate, Pixel, Computational complexity theory and Dynamic programming. His research investigates the connection between Convolutional neural network and topics such as Task analysis that intersect with issues in Feature extraction and Pose. When carried out as part of a general Segmentation research project, his work on Image segmentation is frequently linked to work in Colonoscopy, therefore connecting diverse disciplines of study.

Between 2015 and 2021, his most popular works were:

  • The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes (1055 citations)
  • CARLA: An Open Urban Driving Simulator (766 citations)
  • End-to-End Driving Via Conditional Imitation Learning (309 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

Antonio M. Lopez spends much of his time researching Artificial intelligence, Machine learning, Computer vision, Human–computer interaction and Imitation learning. By researching both Artificial intelligence and Pedestrian detection, he produces research that crosses academic boundaries. His work on Convolutional neural network as part of general Machine learning study is frequently linked to Generative model, bridging the gap between disciplines.

His study in Computer vision is interdisciplinary in nature, drawing from both Feature learning and Code. His biological study spans a wide range of topics, including Driving simulator and Reinforcement learning. The various areas that Antonio M. Lopez examines in his Imitation learning study include End-to-end principle, Causal model, Overfitting 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.

Best Publications

Survey of Pedestrian Detection for Advanced Driver Assistance Systems

David Gerónimo;Antonio M López;Angel D Sappa;Thorsten Graf.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)

1235 Citations

The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes

German Ros;Laura Sellart;Joanna Materzynska;David Vazquez.
computer vision and pattern recognition (2016)

1123 Citations

CARLA: An Open Urban Driving Simulator

Alexey Dosovitskiy;Germán Ros;Felipe Codevilla;Antonio M. López.
Conference on Robot Learning (2017)

955 Citations

End-to-End Driving Via Conditional Imitation Learning

Felipe Codevilla;Matthias Miiller;Antonio Lopez;Vladlen Koltun.
international conference on robotics and automation (2018)

407 Citations

Color attributes for object detection

Fahad Shahbaz Khan;Rao Muhammad Anwer;Joost van de Weijer;Andrew D. Bagdanov.
computer vision and pattern recognition (2012)

346 Citations

Road Detection Based on Illuminant Invariance

José M Álvarez Alvarez;Antonio M Ĺopez.
IEEE Transactions on Intelligent Transportation Systems (2011)

333 Citations

Evaluation of methods for ridge and valley detection

A.M. Lopez;F. Lumbreras;J. Serrat;J.J. Villanueva.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1999)

324 Citations

Road scene segmentation from a single image

Jose M. Alvarez;Theo Gevers;Yann LeCun;Antonio M. Lopez.
european conference on computer vision (2012)

249 Citations

Learning appearance in virtual scenarios for pedestrian detection

Javier Marin;David Vazquez;David Geronimo;Antonio M. Lopez.
computer vision and pattern recognition (2010)

210 Citations

Virtual and Real World Adaptationfor Pedestrian Detection

David Vázquez;Antonio M. Lopez;Javier Marín;Daniel Ponsa.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)

197 Citations

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Best Scientists Citing Antonio M. López

Luc Van Gool

Luc Van Gool

ETH Zurich

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Joost van de Weijer

Joost van de Weijer

Autonomous University of Barcelona

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Fahad Shahbaz Khan

Zayed University

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Raquel Urtasun

Raquel Urtasun

University of Toronto

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Miguel Angel Sotelo

Miguel Angel Sotelo

University of Alcalá

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Andreas Geiger

Andreas Geiger

University of Tübingen

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Ming Liu

Ming Liu

Hong Kong University of Science and Technology

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Bernt Schiele

Bernt Schiele

Max Planck Institute for Informatics

Publications: 17

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 16

Sergey Levine

Sergey Levine

University of California, Berkeley

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Qi Wang

Qi Wang

Northwestern Polytechnical University

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Sergiu Nedevschi

Sergiu Nedevschi

Technical University of Cluj-Napoca

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Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

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Sanja Fidler

Sanja Fidler

University of Toronto

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Fei-Yue Wang

Fei-Yue Wang

Chinese Academy of Sciences

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Nanning Zheng

Nanning Zheng

Xi'an Jiaotong University

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