Maria Eskevich
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Information Systems
- Communication
- Co-authors
- Gareth J. F. JonesRoeland OrdelmanRobin AlyShu ChenBenoît HuetMartha LarsonHamed BonabRosie Jones
- Topics
- Topic Modeling (11 papers)Video Analysis and Summarization (11 papers)Natural Language Processing Techniques (11 papers)
- Partner nations
- IrelandNetherlandsFrance
In The Last Decade
Maria Eskevich
26 papers receiving 192 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 127
- Computer Vision and Pattern Recognition 126
- Signal Processing 50
- Information Systems 21
- Communication 12
Countries citing papers authored by Maria Eskevich
This map shows the geographic impact of Maria Eskevich'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 Maria Eskevich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Eskevich more than expected).
Fields of papers citing papers by Maria Eskevich
This network shows the impact of papers produced by Maria Eskevich. 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 Maria Eskevich. The network helps show where Maria Eskevich may publish in the future.
Co-authorship network of co-authors of Maria Eskevich
This figure shows the co-authorship network connecting the top 25 collaborators of Maria Eskevich. A scholar is included among the top collaborators of Maria Eskevich 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 Maria Eskevich. Maria Eskevich is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 34 | |
| 4 | TREC 2020 Podcasts Track Overview. | 1 |
| 5 | CLARIN: Distributed Language Resources and Technology in a European Infrastructure | 4 |
| 6 | Challenges of Applying Automatic Speech Recognition for Transcribing EU Parliament Committee Meetings: A Pilot Study | 0 |
| 7 | 6 | |
| 8 | Is all that Glitters in Machine Translation Quality Estimation really Gold | 8 |
| 9 | EURECOM at TRECVID 2016. The Adhoc Video Search and Video Hyperlinking Tasks | 2 |
| 10 | EURECOM @ SAVA2015: Visual Features for Multimedia Search | 1 |
| 11 | 2 | |
| 12 | SAVA at MediaEval 2015: Search and Anchoring in Video Archives | 3 |
| 13 | 9 | |
| 14 | Time-based Segmentation and Use of Jump-in Points in DCU Search Runs at the Search and Hyperlinking Task at MediaEval 2013 | 4 |
| 15 | 11 | |
| 16 | Search and hyperlinking task at MediaEval 2012 | 54 |
| 17 | 1 | |
| 18 | DCU at MediaEval 2011: Rich Speech Retrieval (RSR) | 3 |
| 19 | DCU at the NTCIR-9 SpokenDoc Passage Retrieval Task | 2 |
| 20 | Overview of MediaEval 2011 Rich Speech Retrieval Task and Genre Tagging Task | 37 |
About Maria Eskevich
Maria Eskevich is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 29 papers that have together received 226 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Video Analysis and Summarization (11 papers) and Natural Language Processing Techniques (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (126 citations), Signal Processing (50 citations) and Artificial Intelligence (127 citations). Maria Eskevich has collaborated with scholars based in Ireland, Netherlands and France. Frequent co-authors include Gareth J. F. Jones, Roeland Ordelman, Robin Aly, Shu Chen, Benoît Huet, Martha Larson, Hamed Bonab, Rosie Jones, Jussi Karlgren and Aasish Pappu. Their work appears in journals such as Language Resources and Evaluation, Computer Speech & Language and IEEE Multimedia.
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.