Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A Theoretical Comparison of Texture Algorithms
1980628 citationsRichard W. Conners et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Richard W. Conners
Since
Specialization
Citations
This map shows the geographic impact of Richard W. Conners'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 Richard W. Conners with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard W. Conners more than expected).
Fields of papers citing papers by Richard W. Conners
This network shows the impact of papers produced by Richard W. Conners. 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 Richard W. Conners. The network helps show where Richard W. Conners may publish in the future.
Co-authorship network of co-authors of Richard W. Conners
This figure shows the co-authorship network connecting the top 25 collaborators of Richard W. Conners.
A scholar is included among the top collaborators of Richard W. Conners based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Richard W. Conners. Richard W. Conners is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Liu, Yuming, et al.. (2013). Tampering Detection of Digital Recordings Using Electric Network Frequency and Phase Angle. Journal of the Audio Engineering Society.10 indexed citations
2.
Liu, Fan, et al.. (2013). Source of ENF in Battery-Powered Digital Recordings. Journal of the Audio Engineering Society.22 indexed citations
3.
Xu, Chao, Zhong Zhou, Virgilio Centeno, Richard W. Conners, & Yinsheng Liu. (2005). Practical issues in frequency disturbance recorder design for wide-area monitoring. 11. 69–76.13 indexed citations
Zhu, Dongping, Richard W. Conners, & Philip A. Araman. (1991). 3-D Signal Processing in A Computer Vision System.5 indexed citations
18.
Conners, Richard W., et al.. (1990). A Multisensor Machine Vision System for Hardwood Defect Detection.4 indexed citations
19.
McMillin, Charles W., et al.. (1988). Automated computer grading of hardwood lumber. Forest Products Journal. 38(3). 67–69.31 indexed citations
20.
McMillin, Charles W., et al.. (1984). ALPS- A potential new automated lumber processing system. Forest Products Journal. 34(1). 13–20.19 indexed citations
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.