R. Padilla

16 papers receiving 1.4k citations

Hit Papers

A Survey on Performance Metrics for Object-Detection Algo...202020262022202420202021250500750

Peers

R. Padilla
Comparison fields: 5 of 148
  • Computer Vision and Pattern Recognition 599
  • Artificial Intelligence 210
  • Plant Science 148
  • Industrial and Manufacturing Engineering 148
  • Control and Systems Engineering 118
Replace Sérgio L. Netto with:
Sérgio L. Netto Brazil
Ying Cai China
Fangyao Liu China
Julio-Alejandro Romero-González Mexico
Diana‐Margarita Córdova‐Esparza Mexico
Muhammad Hussain United Kingdom
Bo Ma China
Juan Terven Mexico
L. Minh Dang South Korea
R. Padilla relative to Sérgio L. Netto Brazil Sérgio L. Netto's profile →
Citations per field
00.5×1.5×
Sérgio L. Netto · 1×
Citations per year

Countries citing papers authored by R. Padilla

Since Specialization
Citations

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

Fields of papers citing papers by R. Padilla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Padilla. 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 R. Padilla. The network helps show where R. Padilla may publish in the future.

Co-authorship network of co-authors of R. Padilla

This figure shows the co-authorship network connecting the top 25 collaborators of R. Padilla. A scholar is included among the top collaborators of R. Padilla 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 R. Padilla. R. Padilla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 1
2 1
3 9
4
A Comparative Analysis of Object Detection Metrics with a Companion Open-Source Toolkitbreakdown →
425
5
A Survey on Performance Metrics for Object-Detection Algorithmsbreakdown →
842
6 0
7 1
8 42
9 1
10 7
11 73
12 2
13 6
14 4
15 2
16 4
17 0
18 3

About R. Padilla

R. Padilla is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 18 papers that have together received 1.4k indexed citations. Recurring topics across this work include Control Systems and Identification (5 papers), Advanced Control Systems Optimization (4 papers) and Fault Detection and Control Systems (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (599 citations), Industrial and Manufacturing Engineering (148 citations) and Media Technology (101 citations). R. Padilla has collaborated with scholars based in Brazil, Venezuela and United States. Frequent co-authors include Sérgio L. Netto, Eduardo A. B. da Silva, Wesley L. Passos, Rodolfo Milito, Cícero Ferreira Fernandes Costa Filho, M. G. F. Costa, A. Haddad, J.B. Cruz, S. Bingulac and Marcello L. R. de Campos. Their work appears in journals such as IEEE Transactions on Automatic Control, Journal of Petroleum Science and Engineering and International Journal of Control.

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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