Phillip L. De León

63 papers receiving 876 citations

Peers

Phillip L. De León
Comparison fields: 5 of 80
  • Signal Processing 630
  • Artificial Intelligence 561
  • Computer Vision and Pattern Recognition 138
  • Electrical and Electronic Engineering 118
  • Computer Networks and Communications 104
Replace Atsunori Ogawa with:
Atsunori Ogawa Japan
Gernot Kubin Austria
Soo Ngee Koh Singapore
Esam Abdel‐Raheem Canada
Aaron E. Cohen United States
T.V. Sreenivas India
J.F. Doherty United States
Zoran Perić Serbia
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Phillip L. De León relative to Atsunori Ogawa Japan Atsunori Ogawa's profile →
Citations per field
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Citations per year

Countries citing papers authored by Phillip L. De León

Since Specialization
Citations

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

Fields of papers citing papers by Phillip L. De León

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phillip L. De León. 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 Phillip L. De León. The network helps show where Phillip L. De León may publish in the future.

Co-authorship network of co-authors of Phillip L. De León

This figure shows the co-authorship network connecting the top 25 collaborators of Phillip L. De León. A scholar is included among the top collaborators of Phillip L. De León 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 Phillip L. De León. Phillip L. De León 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
#WorkIndexed citations
1 7
2 8
3 3
4 75
5
A Smartphone-Based Gait Data Collection System for the Prediction of Falls in Elderly Adults
3
6 103
7
Evaluation of the Vulnerability of Speaker Verification to Synthetic Speech
38
8 9
9
Compensation for room reverberation in speaker identification
3
10 2
11 6
12
A DESIGN FOR SATELLITE GROUND STATION RECEIVER AUTOCONFIGURATION
1
13 0
14 3
15 1
16 35
17 1
18 36
19
Design of a phonetic corpus for speech recognition in catalan
1
20 35

About Phillip L. De León

Phillip L. De León is a scholar working on Signal Processing, Artificial Intelligence and Physical Therapy, Sports Therapy and Rehabilitation, having authored 67 papers that have together received 934 indexed citations. Recurring topics across this work include Speech and Audio Processing (36 papers), Speech Recognition and Synthesis (30 papers) and Music and Audio Processing (15 papers). The work is most often cited by research in Signal Processing (630 citations), Artificial Intelligence (561 citations) and Computer Vision and Pattern Recognition (138 citations). Phillip L. De León has collaborated with scholars based in United States, Austria and United Kingdom. Frequent co-authors include Junichi Yamagishi, Michael Pucher, Ibon Saratxaga, Inma Hernáez, Steven Sandoval, Cormac J. Sreenan, D.M. Etter, J. P. F. LeBlanc, Laura E. Boucheron and Sukumar Brahma. Their work appears in journals such as IEEE Transactions on Signal Processing, The Journal of the Acoustical Society of America and IEEE Transactions on Power Delivery.

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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