en.ktu.edu lt search KTU Virtual Tour
ieškoti

Antanas Verikas

Professor

Antanas Verikas – professor, doctor of technical sciences. The main field of research is artificial intelligence methods and their applications in industry, health care, business, nature conservation and other areas of human activity.

The professor publishes publications in prestigious international scientific journals, is the supervisor of many doctoral students who have successfully defended their doctoral theses in Lithuania and Sweden.

A. Verikas is a member of various international professional organizations, such as the Institute of Electrical and Electronics Engineering (IEEE), the International Association for Image Recognition (IAPR) or the International Association for Science and Technology Development (IASTED), a member of the organizing committee of many international scientific conferences, the chairman and guest speaker.

Research Areas

  • Biomedical Engineering
  • Data analysis and processing

Projects

Novel Speech Signal Processing Techniques for Parkinson‘s Disease Identification (Parkinson)

Mokslininkas vadovavo projektui „Nauji kalbos signalo analizės metodai Parkinsono ligai identifikuoti (Parkinson)“, kuriame sukurtas metodas, leidžiantis atpažinti balso sutrikimus, kurie yra vienas iš pačių ankstyviausių Parkinsono ligos simptomų.

A deep learning-based automated system for seabed imagery recognition and quantitative analysis (DEMERSAL)

The project consortium brings together specialists in signal, image and video processing, and marine benthic ecologists with long-term experience in UW research. Scientists plan to develop a user-friendly system, flexible enough to use in a variety of marine environments. To test system’s capabilities, video material collected in the Arctic Ocean, Baltic Sea, Mediterranean Sea and other world regions will be used. Project results: a unique, precisely annotated, database of seabed images, which will be of international value for the development and training of systems for seabed video analysis; a novel, unsupervised learning-based, method allowing to exploit unlabelled (unannotated) seabed images for training DCNN, dedicated to analysis of seabed videos.

Articles

No. Title Authors Year
1. Assessing Parkinson’s disease severity using speech analysis in non-native speakers Taha Khan, Lina E. Lundgren, David G. Anderson, Irena Nowak, Mark Dougherty, Antanas Verikas, Misha Pavel, Holly B. Jimison, Slawomir Nowaczyk, Vered Aharonson 2020
2. Agreeing to disagree: active learning with noisy labels without crowdsourcing Mohamed-Rafik Bouguelia, Slawomir Nowaczyk, K. C. Santosh, Antanas Verikas 2018
3. Automatic benthic imagery recognition using a hierarchical two-stage approach Tadas Rimavičius, Adas Gelžinis, Antanas Verikas, Evaldas Vaičiukynas, Marija Bačauskienė, Aleksej Saskov 2018
4. Predicting physiological parameters in fatiguing bicycling exercises using muscle activation timing Petras Ražanskas, Antanas Verikas, Per-Arne Viberg, Charlotte Olsson 2017

Publications in media

Antanas Verikas KTU