Renato Panda

737 citations
25 papers · 460 · h-index 10

Impact in

Papers in

Renato Panda

24 papers receiving 424 citations

Peers

Renato Panda
Comparison fields: 5 of 54
  • Signal Processing 331
  • Cognitive Neuroscience 187
  • Computer Vision and Pattern Recognition 171
  • Experimental and Cognitive Psychology 94
  • Music 17
Replace Ya-Fan Su with:
Ya-Fan Su Taiwan
Ricardo Malheiro Portugal
Anna Aljanaki Netherlands
Μάξιμος Καλιακάτσος-Παπακώστας Greece
Jeffrey J. Scott United States
Estefanía Cano Germany
Arne Eigenfeldt Canada
Óscar Mayor Spain
Cyril Laurier Spain
Danning Jiang China
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Citations per field
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Citations per year

Countries citing papers authored by Renato Panda

Since Specialization
Citations

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

Fields of papers citing papers by Renato Panda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Renato Panda, 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 Renato Panda Line = papers co-authored together Renato Panda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018121
2 202080
3 201658
4
Multi-Modal Music Emotion Recognition: A New Dataset, Methodology and Comparative Analysis
201326
5 201524
6 201824
7
Using Support Vector Machines for Automatic Mood Tracking in Audio Music
201120
8 201811
9
Music Emotion Classification: Dataset Acquisition and Comparative Analysis
201211
10 201410
11 20199
12 20169
13 20219
14 20148
15
Music Emotion Recognition from Lyrics: A Comparative Study
20138
16 20227
17
Bi-modal music emotion recognition: Novel lyrical features and dataset
20167
18
MOODetector: A Prototype Software Tool for Mood-based Playlist Generation
20115
19 20244
20
Music Emotion Classification: Analysis of a Classifier Ensemble Approach
20123

About Renato Panda

Renato Panda is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience and Computer Networks and Communications, having authored 25 papers that have together received 460 indexed citations. Recurring topics across this work include Music and Audio Processing (20 papers), Speech and Audio Processing (14 papers), Music Technology and Sound Studies (7 papers), Neuroscience and Music Perception (6 papers), Speech Recognition and Synthesis (5 papers), IoT and Edge/Fog Computing (3 papers), Context-Aware Activity Recognition Systems (3 papers) and Technology Use by Older Adults (2 papers). The work is most often cited by research in Signal Processing (331 citations), Cognitive Neuroscience (187 citations), Computer Vision and Pattern Recognition (171 citations), Experimental and Cognitive Psychology (94 citations) and Music (17 citations). Renato Panda has collaborated with scholars based in Portugal and Brazil. Frequent co-authors include Rui Pedro Paiva, Ricardo Malheiro, Bruno Rocha, Antônio Pedro Novaes de Oliveira, Gabriel Pires, Luís Oliveira, Ana Lopes, Paulo Monteiro, Telmo Pereira and Pedro Ferreira. Their work appears in journals such as IEEE Transactions on Affective Computing, Applied Artificial Intelligence, Sensors, Journal of the Audio Engineering Society and Lecture notes in computer science.

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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