Perfecto Herrera
About
In The Last Decade
Perfecto Herrera
135 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Signal Processing 2.2k
- Computer Vision and Pattern Recognition 1.8k
- Cognitive Neuroscience 725
- Artificial Intelligence 494
- Information Systems 270
Countries citing papers authored by Perfecto Herrera
This map shows the geographic impact of Perfecto Herrera'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 Perfecto Herrera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Perfecto Herrera more than expected).
Fields of papers citing papers by Perfecto Herrera
This network shows the impact of papers produced by Perfecto Herrera. 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 Perfecto Herrera. The network helps show where Perfecto Herrera may publish in the future.
Co-authorship network of co-authors of Perfecto Herrera
This figure shows the co-authorship network connecting the top 25 collaborators of Perfecto Herrera. A scholar is included among the top collaborators of Perfecto Herrera 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 Perfecto Herrera. Perfecto Herrera 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 | The emotions that we perceive in music: the influence of language and lyrics comprehension on agreement | 1 |
| 4 | MULTI-CLASS SUPPORT VECTOR MACHINE ACTIVE LEARNING FOR MUSIC ANNOTATION | 11 |
| 5 | Mood Cloud : A Real-Time Music Mood Visualization Tool | 8 |
| 6 | Modeling the acquisition of statistical regularities in tone sequences | 1 |
| 7 | EXPECTATION ALONG THE BEAT: A USE CASE FOR MUSIC EXPECTATION MODELS | 5 |
| 8 | Automatic Tonal Analysis from Music Summaries for Version Identification | 12 |
| 9 | The Rhythm Transform: Towards A Generic Rhythm Description | 2 |
| 10 | SEMANTIC SEGMENTATION OF MUSIC AUDIO CONTENTS | 19 |
| 11 | TOWARDS A SEMANTIC DESCRIPTOR OF SUBJECTIVE INTENSITY IN MUSIC | 4 |
| 12 | Getting music recommendations and filtering newsfeeds from FOAF descriptions | 5 |
| 13 | Detrended Fluctuation Analysis of Music Signals: Danceability Estimation and Further Semantic Characterization | 17 |
| 14 | Morphological Sound Description: Computational Model and Usability Evaluation | 7 |
| 15 | Automatic Extraction of Tonal Metadata from Polyphonic Audio Recordings | 12 |
| 16 | Knowledge and Content-Based Audio Retrieval Using Wordnet. | 4 |
| 17 | Nearest-neighbor Generic Sound Classification with a WordNet-based Taxonomy | 19 |
| 18 | Automatic Labeling of Unpitched Percussion Sounds | 11 |
| 19 | Determination of the Meter of Musical Audio Signals: Seeking Recurrences in Beat Segment Descriptors | 34 |
| 20 | Audio Descriptors and Descriptor Schemes in the Context of MPEG-7 | 27 |
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.