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.
Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings
2017336 citationsDavid Verstraete, Enrique López Droguett et al.Shock and Vibrationprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Mohammad Modarres
Since
Specialization
Citations
This map shows the geographic impact of Mohammad Modarres'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 Mohammad Modarres with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Modarres more than expected).
Fields of papers citing papers by Mohammad Modarres
This network shows the impact of papers produced by Mohammad Modarres. 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 Mohammad Modarres. The network helps show where Mohammad Modarres may publish in the future.
Co-authorship network of co-authors of Mohammad Modarres
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Modarres.
A scholar is included among the top collaborators of Mohammad Modarres 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 Mohammad Modarres. Mohammad Modarres is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Verstraete, David, et al.. (2017). Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings. Shock and Vibration. 2017. 1–17.336 indexed citations breakdown →
9.
Modarres, Mohammad. (2016). Sensor-Based Bayesian Inference and Placement: Review and Examples. International Journal of Performability Engineering. 12(1). 13.1 indexed citations
10.
Modarres, Mohammad, et al.. (2015). Optimizing land leveling by applying warped surface. SHILAP Revista de lepidopterología.1 indexed citations
Martins, Marcelo Ramos, et al.. (2012). The Use of Bayesian Networks In Reliability Analysis of the LNG Regasification System On a FSRU Under Different Scenarios. The Twenty-second International Offshore and Polar Engineering Conference.1 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.