Advances in computer vision and pattern recognition

18.5k citations
767 papers · · active since 2016

Impact in

    • Multimodal Machine Learning Applications
    • Video Surveillance and Tracking Methods
    • Human Pose and Action Recognition
    • Face recognition and analysis
    • Advanced Image and Video Retrieval Techniques
    • Advanced Neural Network Applications
    • Biometric Identification and Security

Papers in

    • Advanced Image and Video Retrieval Techniques 109
    • Face recognition and analysis 84
    • Image Retrieval and Classification Techniques 69
    • Advanced Vision and Imaging 64
    • Video Surveillance and Tracking Methods 62
    • Face and Expression Recognition 60
    • Biometric Identification and Security 154

Advances in computer vision and pattern recognition

685 papers receiving 15.9k citations

Peers

Advances in computer vision and pattern recognition
Comparison fields: 5 of 211
  • Computer Vision and Pattern Recognition 9.5k
  • Signal Processing 2.9k
  • Artificial Intelligence 7.2k
  • Media Technology 925
  • Human-Computer Interaction 585
Replace Computer Science Review with:
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Wiley Interdisciplinary Reviews Computational Statistics United States
IEEE Consumer Electronics Magazine United States
IEEE Computational Intelligence Magazine China
CAAI Transactions on Intelligence Technology China
Cognitive Systems Research United States
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Advances in computer vision and pattern recognition relative to Computer Science Review India Computer Science Review's profile →
Citations per field
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Citations per year

Countries where authors publish in Advances in computer vision and pattern recognition

Since Specialization
Citations

This map shows the geographic impact of research published in Advances in computer vision and pattern recognition. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Advances in computer vision and pattern recognition with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Advances in computer vision and pattern recognition more than expected).

Fields of papers published in Advances in computer vision and pattern recognition

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Advances in computer vision and pattern recognition. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Advances in computer vision and pattern recognition.

About Advances in computer vision and pattern recognition

The 767 papers published in Advances in computer vision and pattern recognition in the last decades have received a total of 18.5k indexed citations . Papers published in Advances in computer vision and pattern recognition usually cover Computer Vision and Pattern Recognition (498 papers), Signal Processing (180 papers), Media Technology (61 papers), Artificial Intelligence (181 papers) and Safety Research (40 papers) specifically the topics of Biometric Identification and Security (154 papers), Advanced Image and Video Retrieval Techniques (109 papers), Face recognition and analysis (84 papers), Image Retrieval and Classification Techniques (69 papers), Advanced Vision and Imaging (64 papers), Video Surveillance and Tracking Methods (62 papers), Face and Expression Recognition (60 papers) and User Authentication and Security Systems (54 papers). The most active scholars publishing in Advances in computer vision and pattern recognition are Shigeo Abe, Victor Lempitsky, Mario Marchand, Pascal Germain, Hugo Larochelle, François Laviolette, Evgeniya Ustinova, Yaroslav Ganin, Bernardino Romera‐Paredes and Philip H. S. Torr.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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