I.Mednieks is with IECS starting from 1980 as an engineer. He has been mainly involved in R&D projects related with pseudorandomized DSP and DASP technology. His current research activities are concentrated on image processing. Dr.sc.ing. (1988), Dr..sc.comp. (1992). Author of more than 50 publications. Main interests: • Randomized Digital Signal Processing • Non-orthogonal transforms • Digital Alias-free Signal Processing (DASP) technology • Virtual instrumentation • Image processing for object detection • 3D imaging • Remote sensing • Image classification
- Object based context aware self-learning network for land cover classification (Dynland-2)
- Satellite remote sensing- based forest stock estimation technology (WoodStock) #ESIF
- Automated identification of mires and peatlands using multi-temporal satellite data (MireClass) #ESA
- Dynamic land use monitoring by fusion of satellite data (DynLand) #ESA
- Cyber-physical systems, ontologies and biophotonics for safe&smart city and society (GUDPILS) #SRP (VPP)
- Innovative technologies for acquisition and processing of biomedical images (InBiT) #ESIF
- Multi-model development technology for .NET application projects (MEDUS) #ESIF
- Identification of tree species in Latvian forests (TrIdent) #ESIF
- Remote sensing based system for forest risk factor monitoring (Forest Risk) #ESIF
- Sentinel for confidence in outdated maps: SentiMap #ESIF
- Linda Gulbe, Juris Zarins, Ints Mednieks, “Automated delineation of microstands in hemiboreal mixed forests using stereo GeoEye-1 data”. MPDI Open Access Journals, Remote Sens. 18 March 2022. https://www.mdpi.com/2072-4292/14/6/1471.
- Sinica-Sinavskis J., Dinuls R., Zarins J., Mednieks I., Automatic tree species classification from Sentinel 2 images using deficient inventory data, 2020 17th Biennial Baltic Electronics Conference (BEC), Tallinn, Estonia, pp. 1-6, 2020.