IEEE Transactions on Pattern Analysis and Machine Intelligence

1.5M citations
10.0k papers · · active since 1979

Impact in

    • Video Surveillance and Tracking Methods
    • Advanced Neural Network Applications
    • Medical Image Segmentation Techniques
    • Advanced Vision and Imaging
    • Face and Expression Recognition
    • Face recognition and analysis
    • Image Retrieval and Classification Techniques
    • Handwritten Text Recognition Techniques

Papers in

    • Advanced Vision and Imaging 666
    • Advanced Neural Network Applications 516
    • Video Surveillance and Tracking Methods 336
    • Handwritten Text Recognition Techniques 304
    • Advanced Image and Video Retrieval Techniques 301
    • Medical Image Segmentation Techniques 283

IEEE Transactions on Pattern Analysis and Machine Intelligence

7.5k papers receiving 1.2M citations

Peers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison fields: 5 of 237
  • Computer Vision and Pattern Recognition 662.8k
  • Computational Mathematics 3.9k
  • Signal Processing 45.1k
  • Media Technology 34.4k
  • Artificial Intelligence 131.4k
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IEEE Transactions on Pattern Analysis and Machine Intelligence relative to IEEE Transactions on Image Processing China IEEE Transactions on Image Processing's profile →
Citations per field
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IEEE Transactions on Image Processing · 1×
Citations per year

Countries where authors publish in IEEE Transactions on Pattern Analysis and Machine Intelligence

Since Specialization
Citations

This map shows the geographic impact of research published in IEEE Transactions on Pattern Analysis and Machine Intelligence. 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 IEEE Transactions on Pattern Analysis and Machine Intelligence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites IEEE Transactions on Pattern Analysis and Machine Intelligence more than expected).

Fields of papers published in IEEE Transactions on Pattern Analysis and Machine Intelligence

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in IEEE Transactions on Pattern Analysis and Machine Intelligence. 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 IEEE Transactions on Pattern Analysis and Machine Intelligence.

About IEEE Transactions on Pattern Analysis and Machine Intelligence

The 10.0k papers published in IEEE Transactions on Pattern Analysis and Machine Intelligence in the last decades have received a total of 1.5M indexed citations . Papers published in IEEE Transactions on Pattern Analysis and Machine Intelligence usually cover Computer Vision and Pattern Recognition (4.7k papers), Computational Mathematics (29 papers), Artificial Intelligence (1.6k papers), Signal Processing (209 papers) and Computational Mechanics (440 papers) specifically the topics of Advanced Vision and Imaging (666 papers), Advanced Neural Network Applications (516 papers), 3D Shape Modeling and Analysis (379 papers), Video Surveillance and Tracking Methods (336 papers), Domain Adaptation and Few-Shot Learning (334 papers), Handwritten Text Recognition Techniques (304 papers), Advanced Image and Video Retrieval Techniques (301 papers) and Medical Image Segmentation Techniques (283 papers). The most active scholars publishing in IEEE Transactions on Pattern Analysis and Machine Intelligence are John Canny, Kaiming He, Stéphane Mallat, Ross Girshick, Jitendra Malik, Shaoqing Ren, Jian Sun, Anil Kumar Jain, Zheng Zhang and Paul J. Besl.

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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