Francesco Nesta

1.1k citations
34 papers · 606 indexed · h-index 12

Francesco Nesta

32 papers receiving 527 citations

Peers

Francesco Nesta
Comparison fields: 5 of 33
  • Signal Processing 568
  • Computational Mechanics 226
  • Artificial Intelligence 227
  • Analytical Chemistry 26
  • Cognitive Neuroscience 47
Replace Aditya Arie Nugraha with:
Aditya Arie Nugraha Japan
Robert Aichner Germany
Daichi Kitamura Japan
Tsuyoki Nishikawa Japan
Ngoc Q. K. Duong France
Yu Takahashi Japan
Muhammad Z. Ikram United States
Rintaro Ikeshita Japan
Maria G. Jafari United Kingdom
Te-Won Lee United States
Francesco Nesta relative to Aditya Arie Nugraha Japan Aditya Arie Nugraha's profile →
Citations per field
00.5×3.7×
Aditya Arie Nugraha · 1×
Citations per year

Countries citing papers authored by Francesco Nesta

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Nesta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 22 scholars most cited alongside Francesco Nesta, 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 Francesco Nesta Line = papers co-authored together Francesco Nesta links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 202019
4 20201
5 201714
6 20160
7 20163
8
The second ‘CHiME’ speech separation and recognition challenge: Datasets, tasks and baselines
201311
9 201343
10 2013195
11 201319
12 201211
13 201213
14
Real-Time Prototype for Integration of Blind Source Extraction and Robust Automatic Speech Recognition.
20111
15 20116
16 201148
17 20118
18 201051
19 200911
20 20099

About Francesco Nesta

Francesco Nesta is a scholar working on Signal Processing, Computational Mechanics, Analytical Chemistry, Oceanography and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 606 indexed citations. Recurring topics across this work include Speech and Audio Processing (34 papers), Blind Source Separation Techniques (27 papers), Advanced Adaptive Filtering Techniques (15 papers), Music and Audio Processing (7 papers), Speech Recognition and Synthesis (4 papers), Underwater Acoustics Research (3 papers), Spectroscopy and Chemometric Analyses (3 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Signal Processing (568 citations), Computational Mechanics (226 citations), Artificial Intelligence (227 citations), Analytical Chemistry (26 citations) and Cognitive Neuroscience (47 citations). Francesco Nesta has collaborated with scholars based in Italy, United States and Czechia. Frequent co-authors include Maurizio Omologo, Marco Matassoni, Jon Barker, Shinji Watanabe, Jonathan Le Roux, Emmanuel Vincent, Piergiorgio Svaizer, Zbyněk Koldovský, Biing‐Hwang Juang and Alessio Brutti. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, Computer Speech & Language, IEEE Journal of Solid-State Circuits, IEEE Transactions on Signal Processing and BOA (University of Milano-Bicocca).

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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