Marija Bačauskienė
- Artificial Intelligence top 2%
- Speech Recognition and Synthesis 18
- Neural Networks and Applications 13
- Signal Processing top 2%
- Music and Audio Processing 19
- Speech and Audio Processing 9
- Speech and Hearing top 5%
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- Face and Expression Recognition 6
- Physiology top 10%
- Voice and Speech Disorders 18
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- Color Science and Applications 8
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- Industrial Vision Systems and Defect Detection 7
- Co-authors
- Antanas VerikasAdas GelžinisEvaldas VaičiukynasVirgilijus UlozaKerstin MalmqvistArūnas LipnickasIrina OleninaSergej Olenin
- Journals
- Expert Systems with Applications (8 papers)Pattern Recognition (4 papers)Computers in Biology and Medicine (4 papers)
- Partner nations
- LithuaniaSwedenUnited States
In The Last Decade
Marija Bačauskienė
69 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Artificial Intelligence 772
- Signal Processing 254
- Speech and Hearing 102
- Computer Vision and Pattern Recognition 297
- Physiology 359
Countries citing papers authored by Marija Bačauskienė
This map shows the geographic impact of Marija Bačauskienė'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 Marija Bačauskienė with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marija Bačauskienė more than expected).
Fields of papers citing papers by Marija Bačauskienė
This network shows the impact of papers produced by Marija Bačauskienė. 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 Marija Bačauskienė. The network helps show where Marija Bačauskienė may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Marija Bačauskienė, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 5 | |
| 2 | 2017 | 76 | |
| 3 | Towards Voice and Query Data-based Non-invasive Screening for Laryngeal Disorders | 2015 | 1 |
| 4 | 2015 | 4 | |
| 5 | 2014 | 2 | |
| 6 | 2014 | 16 | |
| 7 | 2011 | 26 | |
| 8 | 2010 | 46 | |
| 9 | 2009 | 12 | |
| 10 | 2009 | 39 | |
| 11 | 2008 | 79 | |
| 12 | 2007 | 6 | |
| 13 | 2007 | 43 | |
| 14 | 2006 | 26 | |
| 15 | 2004 | 3 | |
| 16 | Neural Modelling and Control of the Offset Printing Process. | 2003 | 4 |
| 17 | 2003 | 2 | |
| 18 | 2003 | 1 | |
| 19 | Selecting features with neural networks | 2001 | 1 |
| 20 | Soft Fusion of Neural Classifiers | 1998 | 1 |
About Marija Bačauskienė
Marija Bačauskienė is a scholar working on Signal Processing, Sensory Systems, Artificial Intelligence, Otorhinolaryngology and Computer Vision and Pattern Recognition, having authored 71 papers that have together received 1.8k indexed citations. Recurring topics across this work include Music and Audio Processing (19 papers), Speech Recognition and Synthesis (18 papers), Voice and Speech Disorders (18 papers), Neural Networks and Applications (13 papers), Speech and Audio Processing (9 papers), Color Science and Applications (8 papers), Industrial Vision Systems and Defect Detection (7 papers) and Face and Expression Recognition (6 papers). The work is most often cited by research in Artificial Intelligence (772 citations), Signal Processing (254 citations), Speech and Hearing (102 citations), Computer Vision and Pattern Recognition (297 citations) and Physiology (359 citations). Marija Bačauskienė has collaborated with scholars based in Lithuania, Sweden and United States. Frequent co-authors include Antanas Verikas, Adas Gelžinis, Evaldas Vaičiukynas, Virgilijus Uloza, Kerstin Malmqvist, Arūnas Lipnickas, Irina Olenina, Sergej Olenin, Rūta Pribuišienė and Viktoras Šaferis. Their work appears in journals such as Expert Systems with Applications, Pattern Recognition, Computers in Biology and Medicine, Pattern Recognition Letters and Neural Computing and Applications.
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.