Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Emotional speech recognition: Resources, features, and methods
2006627 citationsConstantine Kotropoulos et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Constantine Kotropoulos
Since
Specialization
Citations
This map shows the geographic impact of Constantine Kotropoulos'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 Constantine Kotropoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Constantine Kotropoulos more than expected).
Fields of papers citing papers by Constantine Kotropoulos
This network shows the impact of papers produced by Constantine Kotropoulos. 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 Constantine Kotropoulos. The network helps show where Constantine Kotropoulos may publish in the future.
Co-authorship network of co-authors of Constantine Kotropoulos
This figure shows the co-authorship network connecting the top 25 collaborators of Constantine Kotropoulos.
A scholar is included among the top collaborators of Constantine Kotropoulos 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 Constantine Kotropoulos. Constantine Kotropoulos is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Panagakis, Yannis & Constantine Kotropoulos. (2012). Music structure analysis by subspace modeling. European Signal Processing Conference. 1459–1463.2 indexed citations
Panagakis, Yannis, Constantine Kotropoulos, & Gonzalo R. Arce. (2011). ℓ1-GRAPH BASED MUSIC STRUCTURE ANALYSIS. International Symposium/Conference on Music Information Retrieval. 495–500.7 indexed citations
12.
Panagakis, Yannis & Constantine Kotropoulos. (2011). Automatic music mood classification via Low-Rank Representation. European Signal Processing Conference. 689–693.5 indexed citations
13.
Panagakis, Yannis, Constantine Kotropoulos, & Gonzalo R. Arce. (2010). Sparse multi-label linear embedding nonnegative tensor factorization for automatic music tagging. European Signal Processing Conference. 492–496.4 indexed citations
Benetos, Emmanouil, Margarita Kotti, Constantine Kotropoulos, et al.. (2008). MUSCLE movie-database: a multimodal corpus with rich annotation for dialogue and saliency detection. Language Resources and Evaluation.3 indexed citations
16.
Benetos, Emmanouil, Margarita Kotti, & Constantine Kotropoulos. (2007). Large Scale Musical Instrument Identification. City Research Online (City University London).16 indexed citations
Kotropoulos, Constantine & Ioannis Pitas. (2001). Nonlinear Model-Based Image/Video Processing and Analysis. John Wiley & Sons, Inc. eBooks.33 indexed citations
19.
Kotropoulos, Constantine, et al.. (2001). Hierarchical Word Clustering for Relevance Judgments in Information Retrieval. 139–148.4 indexed citations
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.