Edgars Lielāmurs has been a researcher at the Integrated Circuits and Systems Laboratory of the Institute of Electronics and Computer Science since 2020. He graduated Riga Technical university in 2021 receiving master’s degree in electrical engineering. His main interests are computer vision, neuromorphic computing and digital signal processing algorithms implementation with FPGAs.
Recent projects
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Intelligent, Safe and Secure Connected Electrical Mobility Solutions: Towards European Green Deal and Seamless Mobility (EcoMobility) #ChipsJU
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Artificial Intelligence using Quantum measured Information for realtime distributed systems at the edge (A-IQ Ready) #ChipsJU
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A mosaic of essential electronic components and systems (ECS) for our automated digital future in industry and mobility (MOSAIC) #ChipsJU
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Ensuring European ECS Value Chain Sovereignty through Shaping the Future of ECS for Automotive Applications (ShapeFuture) #ChipsJU
Recent publications
- Edgars Lielāmurs, Andrejs Cvetkovs, Rihards Novickis, Kaspars Ozols, 2023. Infrared Image Pre-Processing and IR/RGB Registration with FPGA Implementation. Electronics, 12(4), 4, MDPI.
- Rihards Novickis, Edgars Lielāmurs, Daniels Jānis Justs, Andrejs Cvetkovs, Kaspars Ozols. "Spatial Transformation Accelerator with Parallel Data Access Scheme for Sample Reconstruction" Electronics 13(5): pp.922 https://doi.org/10.3390/electronics13050922
- Edgars Lielāmurs, Kaspars Ozols. "Spatio-temporal Object Detection with Deep Spiking CNNs Using Time-of-Flight Data" 2024 19th Biennial Baltic Electronics Conference (BEC) pp.1-6. ttps://www.researchgate.net/publication/385653033_Spatio-temporal_Object_Detection_with_Deep_Spiking_CNNs_Using_Time-of-Flight_Data, https://ieeexplore.ieee.org/abstract/document/10737976
- Edgars Lielamurs, Ibrahim Sayed, Andrejs Cvetkovs, Rihards Novickis, Anatolijs Zencovs, Maksis Celitans, Andis Bizuns, George Dimitrakopoulos, Jochen Koszescha, Kaspars Ozols. 2025. "A Distributed Time-of-Flight Sensor System for Autonomous Vehicles: Architecture, Sensor Fusion, and Spiking Neural Network Perception" Electronics, 14(7) https://www.mdpi.com/2079-9292/14/7/1375