Will N. Browne

6.8k citations
150 papers · 4.4k indexed · 3 hit papers · h-index 23

Will N. Browne

143 papers receiving 4.2k citations

Hit Papers

A Survey on Evolutionary Computation Approaches to Featur...1.2k20122026201620214008001.2k

Peers

Will N. Browne
Comparison fields: 5 of 162
  • Artificial Intelligence 3.0k
  • Computational Theory and Mathematics 836
  • Computer Vision and Pattern Recognition 814
  • Health Information Management 88
  • Media Technology 158
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Xiao‐Zhi Gao Finland
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Citations per year

Countries citing papers authored by Will N. Browne

Since Specialization
Citations

This map shows the geographic impact of Will N. Browne's research. 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 Will N. Browne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will N. Browne more than expected).

Fields of papers citing papers by Will N. Browne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Will N. Browne. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Will N. Browne. The network helps show where Will N. Browne may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Will N. Browne, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Will N. Browne Line = papers co-authored together Will N. Browne links everyone, so they are left out of the graph.

All Works

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Robotic competitions: Short term pain for long term gain
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Image region salience for improving appearance-based place recognition using a supervised classifier system
20121
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Investigating the use of magneto-rheological fluid in an active compliant actuator for a stroke rehabilitation system
20112
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About Will N. Browne

Will N. Browne is a scholar working on Artificial Intelligence, Architecture, Sensory Systems, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 150 papers that have together received 4.4k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (80 papers), Metaheuristic Optimization Algorithms Research (75 papers), Viral Infectious Diseases and Gene Expression in Insects (24 papers), Reinforcement Learning in Robotics (14 papers), Neural Networks and Applications (14 papers), Advanced Multi-Objective Optimization Algorithms (13 papers), Visual Attention and Saliency Detection (8 papers) and Emotion and Mood Recognition (8 papers). The work is most often cited by research in Artificial Intelligence (3.0k citations), Computational Theory and Mathematics (836 citations), Computer Vision and Pattern Recognition (814 citations), Health Information Management (88 citations) and Media Technology (158 citations). Will N. Browne has collaborated with scholars based in New Zealand, Australia and United Kingdom. Frequent co-authors include Bing Xue, Mengjie Zhang, Xin Yao, Jun Zhang, Muhammad Iqbal, Soheil Mohseni, Alan C. Brent, Liam Cervante, Lin Shang and Scott Kelly. Their work appears in journals such as Applied Soft Computing, IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, Engineering Applications of Artificial Intelligence and Soft Computing.

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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