H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 58 Citations 13,623 167 World Ranking 1838 National Ranking 76

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Machine learning, Object and Pattern recognition. His work on Artificial intelligence deals in particular with Image, Turing test, Convolutional neural network, Contextual image classification and Support vector machine. His Support vector machine research includes elements of Material classification and Cognitive neuroscience of visual object recognition.

His work in the fields of Computer vision, such as Face and Single image, intersects with other areas such as Laundry and Grippers. His study in Machine learning is interdisciplinary in nature, drawing from both Topic model, Object detection, Key and Computer vision pattern recognition. In his study, which falls under the umbrella issue of Object, Noise is strongly linked to Computer graphics.

His most cited work include:

  • Adapting visual category models to new domains (1539 citations)
  • Discovery of activity patterns using topic models (357 citations)
  • Ask Your Neurons: A Neural-Based Approach to Answering Questions about Images (345 citations)

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

His primary areas of investigation include Artificial intelligence, Machine learning, Computer vision, Pattern recognition and Deep learning. His research related to Object, Image, Segmentation, Training set and Inference might be considered part of Artificial intelligence. He specializes in Object, namely Object detection.

His study in Machine learning focuses on Support vector machine in particular. His work in the fields of Computer vision, such as Gaze, RGB color model and Pose, overlaps with other areas such as Reflectivity. In most of his Pattern recognition studies, his work intersects topics such as Feature.

He most often published in these fields:

  • Artificial intelligence (76.77%)
  • Machine learning (34.25%)
  • Computer vision (24.80%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (76.77%)
  • Machine learning (34.25%)
  • Inference (7.87%)

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

His main research concerns Artificial intelligence, Machine learning, Inference, Deep learning and Generative grammar. His studies deal with areas such as State and Pattern recognition as well as Artificial intelligence. His Contrast study, which is part of a larger body of work in Machine learning, is frequently linked to Side effect, bridging the gap between disciplines.

His studies in Inference integrate themes in fields like Adversary and Algorithm. His study looks at the intersection of Deep learning and topics like Computer vision with Recommender system. His work in Generative grammar addresses issues such as Control, which are connected to fields such as Range.

Between 2019 and 2021, his most popular works were:

  • Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (22 citations)
  • Towards Causal VQA: Revealing and Reducing Spurious Correlations by Invariant and Covariant Semantic Editing (19 citations)
  • GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models (9 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Mario Fritz mostly deals with Machine learning, Artificial intelligence, Inference, Training set and Information retrieval. Mario Fritz interconnects Fingerprint and Generative grammar in the investigation of issues within Machine learning. His Artificial intelligence study often links to related topics such as Spurious relationship.

His research integrates issues of Annotation, Segmentation, State and Asset in his study of Inference. Mario Fritz has researched Training set in several fields, including Deep learning, Countermeasure and Fingerprint. Mario Fritz has included themes like Classifier, Margin, Privacy policy and Metric in his Information retrieval study.

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

Adapting visual category models to new domains

Kate Saenko;Brian Kulis;Mario Fritz;Trevor Darrell.
european conference on computer vision (2010)

1506 Citations

Discovery of activity patterns using topic models

Tâm Huynh;Mario Fritz;Bernt Schiele.
ubiquitous computing (2008)

513 Citations

A Category-Level 3D Object Dataset: Putting the Kinect to Work.

Allison Janoch;Sergey Karayev;Yangqing Jia;Jonathan T. Barron.
Consumer Depth Cameras for Computer Vision (2013)

455 Citations

On the Significance of Real‐World Conditions for Material Classification

Eric Hayman;Barbara Caputo;Mario Fritz;Jan Olof Eklundh.
european conference on computer vision (2004)

402 Citations

The 2005 PASCAL visual object classes challenge

Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool.
international conference on machine learning (2005)

389 Citations

Appearance-based gaze estimation in the wild

Xucong Zhang;Yusuke Sugano;Mario Fritz;Andreas Bulling.
computer vision and pattern recognition (2015)

375 Citations

Ask Your Neurons: A Neural-Based Approach to Answering Questions about Images

Mateusz Malinowski;Marcus Rohrbach;Mario Fritz.
international conference on computer vision (2015)

373 Citations

A category-level 3-D object dataset: Putting the Kinect to work

Allison Janoch;Sergey Karayev;Yangqing Jia;Jonathan T. Barron.
international conference on computer vision (2011)

355 Citations

Disentangled Person Image Generation

Liqian Ma;Qianru Sun;Stamatios Georgoulis;Luc Van Gool.
computer vision and pattern recognition (2018)

294 Citations

A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input

Mateusz Malinowski;Mario Fritz.
arXiv: Artificial Intelligence (2014)

263 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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Contact us

Top Scientists Citing Mario Fritz

Kate Saenko

Kate Saenko

Boston University

Publications: 57

Trevor Darrell

Trevor Darrell

University of California, Berkeley

Publications: 55

Devi Parikh

Devi Parikh

Facebook (United States)

Publications: 46

Dhruv Batra

Dhruv Batra

Georgia Institute of Technology

Publications: 45

Barbara Caputo

Barbara Caputo

Polytechnic University of Turin

Publications: 45

Luc Van Gool

Luc Van Gool

ETH Zurich

Publications: 43

Andreas Bulling

Andreas Bulling

University of Stuttgart

Publications: 42

Anton van den Hengel

Anton van den Hengel

University of Adelaide

Publications: 37

Judy Hoffman

Judy Hoffman

Georgia Institute of Technology

Publications: 37

Bernt Schiele

Bernt Schiele

Max Planck Institute for Informatics

Publications: 37

Chunhua Shen

Chunhua Shen

University of Adelaide

Publications: 34

Mingsheng Long

Mingsheng Long

Tsinghua University

Publications: 32

Kristen Grauman

Kristen Grauman

Facebook (United States)

Publications: 30

Jianmin Wang

Jianmin Wang

Tsinghua University

Publications: 29

Andrew Zisserman

Andrew Zisserman

University of Oxford

Publications: 29

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