Adas Gelžinis

2.3k total citations · 1 hit paper
52 papers, 1.6k citations indexed

About

Adas Gelžinis is a scholar working on Artificial Intelligence, Signal Processing and Physiology. According to data from OpenAlex, Adas Gelžinis has authored 52 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 19 papers in Signal Processing and 17 papers in Physiology. Recurrent topics in Adas Gelžinis's work include Music and Audio Processing (18 papers), Speech Recognition and Synthesis (17 papers) and Voice and Speech Disorders (17 papers). Adas Gelžinis is often cited by papers focused on Music and Audio Processing (18 papers), Speech Recognition and Synthesis (17 papers) and Voice and Speech Disorders (17 papers). Adas Gelžinis collaborates with scholars based in Lithuania, Sweden and China. Adas Gelžinis's co-authors include Antanas Verikas, Marija Bačauskienė, Evaldas Vaičiukynas, Virgilijus Uloza, Kerstin Malmqvist, Arūnas Lipnickas, Viktoras Šaferis, Rūta Pribuišienė, Irina Olenina and Evaldas Padervinskis and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and Sensors.

In The Last Decade

Adas Gelžinis

51 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

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.

Mining data with random forests: A survey and results of new tests

2010 549 citations Antanas Verikas, Adas Gelžinis et al. Pattern Recognition profile →

Peers

Adas Gelžinis

PHYSI

CVPR

ACCOU

Marija Bačauskienė Lithuania

Antanas Verikas Lithuania

Jun Wang United States

Anil Kumar India

Tzu-Tsung Wong Taiwan

Pin Wang China

Birmohan Singh India

Jie Cai China

Syed Mohammed Shamsul Islam Australia

Marija Bačauskienė Lithuania

Adas Gelžinis

772 ×1.2

359 ×0.9

PHYSI

254 ×1.0

297 ×1.2

CVPR

124 ×1.0

ACCOU

Citations per year, relative to Adas Gelžinis Adas Gelžinis (= 1×) peers Marija Bačauskienė

Countries citing papers authored by Adas Gelžinis

Since Specialization

Citations

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

Fields of papers citing papers by Adas Gelžinis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adas Gelžinis

This figure shows the co-authorship network connecting the top 25 collaborators of Adas Gelžinis. A scholar is included among the top collaborators of Adas Gelžinis 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 Adas Gelžinis. Adas Gelžinis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Vaičiukynas, Evaldas, Antanas Verikas, Adas Gelžinis, & Marija Bačauskienė. (2017). Detecting Parkinson’s disease from sustained phonation and speech signals. PLoS ONE. 12(10). e0185613–e0185613. 76 indexed citations

Vaičiukynas, Evaldas, Antanas Verikas, Adas Gelžinis, et al.. (2015). Towards Voice and Query Data-based Non-invasive Screening for Laryngeal Disorders. International Conference on Artificial Intelligence. 32–39. 1 indexed citations

Gelžinis, Adas, Antanas Verikas, Evaldas Vaičiukynas, et al.. (2015). Automatic detection and morphological delineation of bacteriophages in electron microscopy images. Computers in Biology and Medicine. 64. 101–116. 4 indexed citations

Uloza, Virgilijus, Evaldas Padervinskis, Rūta Pribuišienė, et al.. (2015). Exploring the feasibility of smart phone microphone for measurement of acoustic voice parameters and voice pathology screening. European Archives of Oto-Rhino-Laryngology. 272(11). 3391–3399. 62 indexed citations

Olenina, Irina, Evaldas Vaičiukynas, Sigitas Šulčius, et al.. (2015). The dinoflagellate Prorocentrum cordatum at the edge of the salinity tolerance: The growth is slower but cells are larger. Estuarine Coastal and Shelf Science. 168. 71–79. 12 indexed citations

Vaičiukynas, Evaldas, Antanas Verikas, Marija Bačauskienė, Adas Gelžinis, & Zvi Kons. (2014). Enhancing decision-level fusion through cluster-based partitioning of feature set. KTH Publication Database DiVA (KTH Royal Institute of Technology). 259–264. 2 indexed citations

Vaičiukynas, Evaldas, Antanas Verikas, Adas Gelžinis, et al.. (2014). Fusion of voice signal information for detection of mild laryngeal pathology. Applied Soft Computing. 18. 91–103. 16 indexed citations

Verikas, Antanas, Jens Lundström, Marija Bačauskienė, & Adas Gelžinis. (2011). Advances in computational intelligence-based print quality assessment and control in offset colour printing. Expert Systems with Applications. 38(10). 13441–13447. 26 indexed citations

Bačauskienė, Marija, et al.. (2011). Random forests based monitoring of human larynx using questionnaire data. Expert Systems with Applications. 39(5). 5506–5512. 8 indexed citations

10.

Verikas, Antanas, Adas Gelžinis, Marija Bačauskienė, et al.. (2011). Automated image analysis- and soft computing-based detection of the invasive dinoflagellate Prorocentrum minimum (Pavillard) Schiller. Expert Systems with Applications. 39(5). 6069–6077. 9 indexed citations

11.

Uloza, Virgilijus, Antanas Verikas, Marija Bačauskienė, et al.. (2010). Categorizing Normal and Pathological Voices: Automated and Perceptual Categorization. Journal of Voice. 25(6). 700–708. 46 indexed citations

12.

Verikas, Antanas, Adas Gelžinis, & Marija Bačauskienė. (2010). Mining data with random forests: A survey and results of new tests. Pattern Recognition. 44(2). 330–349. 549 indexed citations breakdown →

13.

Verikas, Antanas, et al.. (2009). Using the patient's questionnaire data to screen laryngeal disorders. Computers in Biology and Medicine. 39(2). 148–155. 12 indexed citations

14.

Verikas, Antanas, et al.. (2009). Advances in laryngeal imaging. European Archives of Oto-Rhino-Laryngology. 266(10). 1509–1520. 39 indexed citations

15.

Gelžinis, Adas, Antanas Verikas, & Marija Bačauskienė. (2008). Automated speech analysis applied to laryngeal disease categorization. Computer Methods and Programs in Biomedicine. 91(1). 36–47. 79 indexed citations

16.

Verikas, Antanas, et al.. (2007). A kernel-based approach to categorizing laryngeal images. Computerized Medical Imaging and Graphics. 31(8). 587–594. 6 indexed citations

17.

Gelžinis, Adas, Antanas Verikas, & Marija Bačauskienė. (2007). Increasing the discrimination power of the co-occurrence matrix-based features. Pattern Recognition. 40(9). 2367–2372. 43 indexed citations

18.

Verikas, Antanas, et al.. (2006). Multiple feature sets based categorization of laryngeal images. Computer Methods and Programs in Biomedicine. 85(3). 257–266. 26 indexed citations

19.

Verikas, Antanas, et al.. (2003). An intelligent system for tuning magnetic field of a cathode ray tube deflection yoke. Knowledge-Based Systems. 16(3). 161–164. 2 indexed citations

20.

Verikas, Antanas & Adas Gelžinis. (2000). Training neural networks by stochastic optimisation. Neurocomputing. 30(1-4). 153–172. 3 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.

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