Andrea Apicella
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Roberto PreveteFrancesco IsgròFrancesco DonnarummaPasquale ArpaïaNicola MoccaldiEgidio De BenedettoGiovanni ImprotaAngela La Manna
- Topics
- EEG and Brain-Computer Interfaces (19 papers)Heart Rate Variability and Autonomic Control (8 papers)Advanced Memory and Neural Computing (6 papers)
- Partner nations
- ItalyUzbekistanAustria
In The Last Decade
Andrea Apicella
47 papers receiving 783 citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Cognitive Neuroscience 206
- Artificial Intelligence 196
- Computer Vision and Pattern Recognition 92
- Electrical and Electronic Engineering 81
- Experimental and Cognitive Psychology 78
Countries citing papers authored by Andrea Apicella
This map shows the geographic impact of Andrea Apicella'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 Andrea Apicella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea Apicella more than expected).
Fields of papers citing papers by Andrea Apicella
This network shows the impact of papers produced by Andrea Apicella. 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 Andrea Apicella. The network helps show where Andrea Apicella may publish in the future.
Co-authorship network of co-authors of Andrea Apicella
This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Apicella. A scholar is included among the top collaborators of Andrea Apicella 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 Andrea Apicella. Andrea Apicella is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 10 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 18 | |
| 8 | 17 | |
| 9 | 17 | |
| 10 | 2 | |
| 11 | 11 | |
| 12 | 35 | |
| 13 | 24 | |
| 14 | 11 | |
| 15 | A survey on modern trainable activation functionsbreakdown → | 322 |
| 16 | 6 | |
| 17 | Explaining classification systems using sparse dictionaries. | 2 |
| 18 | 13 | |
| 19 | 1 | |
| 20 | 11 |
About Andrea Apicella
Andrea Apicella is a scholar working on Cognitive Neuroscience, Urology and Experimental and Cognitive Psychology, having authored 52 papers that have together received 805 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (19 papers), Heart Rate Variability and Autonomic Control (8 papers) and Advanced Memory and Neural Computing (6 papers). The work is most often cited by research in Cognitive Neuroscience (206 citations), Health Information Management (36 citations) and Human-Computer Interaction (35 citations). Andrea Apicella has collaborated with scholars based in Italy, Uzbekistan and Austria. Frequent co-authors include Roberto Prevete, Francesco Isgrò, Francesco Donnarumma, Pasquale Arpaïa, Nicola Moccaldi, Egidio De Benedetto, Giovanni Improta, Angela La Manna, Cesare Polito and Luigi Duraccio. Their work appears in journals such as Scientific Reports, The Journal of Urology and IEEE Access.
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.