Ústav počítačových systémů

2025

  • AMIN, H.; AHMED, A.; YUSOFF, M.; MOHAMAD SAAD, M.; MALIK, A. A neurophysiological model based on resting state EEG functional connectivity features for assessing semantic long-term memory performance. Biomedical Signal Processing and Control, 2025, vol. 99, no. 1, p. 1-11. ISSN: 1746-8108. Detail
  • HURTA, M.; OVESNÁ, A.; MRÁZEK, V.; SEKANINA, L. Multi-Objective Evolutionary Design of Explainable EEG Classifier. Genetic Programming, 28th European Conference, EuroGP 2025. Terst: 2025. Detail
  • SEKANINA, L.; JŮZA, T. Genetic Programming with Memory for Approximate Data Reconstruction. In Genetic Programming Theory and Practice XXI. Singapore: Springer Nature Singapore, 2025. p. 199-218. ISBN: 978-981-9600-76-2. Detail

2024

  • ARIF, M.; REHMAN, F.; SEKANINA, L.; MALIK, A. A comprehensive survey of evolutionary algorithms and metaheuristics in brain EEG-based applications. Journal of Neural Engineering, 2024, vol. 21, no. 5, p. 1-25. ISSN: 1741-2552. Detail
  • BAYER, D.; JAROŠ, J. MATLAB Interface To The afft Library. Ostrava: 2024. p. 0-0. Detail
  • DENIZIAK, S.; SITEK, P.; JENIHHIN, M.; STEININGER, A.; SCHÖLZEL, M.; MRÁZEK, V. 27th International Symposium on Design and Diagnostics of Electronic Circuits & Systems. Kliece: Institute of Electrical and Electronics Engineers, 2024. p. 0-0. ISBN: 979-8-3503-5934-3. Detail
  • GOLDSCHMIDT, P.; KUČERA, J. Windower: Feature Extraction for Real-Time DDoS Detection Using Machine Learning. NOMS 2024-2024 IEEE Network Operations and Management Symposium. Seoul: Institute of Electrical and Electronics Engineers, 2024. p. 1-10. ISBN: 979-8-3503-2793-9. Detail
  • HUSA, J.; SEKANINA, L. Semantic Mutation Operator for Fast and Efficient Design of Bent Boolean Functions. Genetic Programming and Evolvable Machines, 2024, vol. 25, no. 3, p. 1-32. ISSN: 1389-2576. Detail
  • HUYNH, N.; ZHANG, E.; FRANCIES, O.; KUKLIŠ, F.; ALLEN, T.; ZHU, J.; ABEYAKOON, O.; LUCKA, F.; BETCKE, M.; JAROŠ, J.; ARRIDGE, S.; COX, B.; PLUMB, A.; BEARD, P. A fast all-optical 3D photoacoustic scanner for clinical vascular imaging. Nature Biomedical Engineering, 2024, vol. 8, no. 10, p. 1-18. ISSN: 2157-846X. Detail
  • JAROŠ, J.; BAYER, D. afft: a C++17 Wrapper Library for FFT-like Computations on Various Targets. Soláň: 2024. p. 0-0. Detail
  • JAROŠ, J.; DUCHOŇ, R. Acceleration of Ultrasound Neurostimulation Using Mixed-Precision Arithmetic. HPDC '24: Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing. New York: Association for Computing Machinery, 2024. p. 370-372. ISBN: 979-8-4007-0413-0. Detail
  • JAROŠ, J.; JAROŠ, M.; BUCHTA, M. Estimation of Distributed Ultrasound Simulation Execution Time Using Machine Learning. In 2024 IEEE Congress on Evolutionary Computation (CEC). Yokohama: Institute of Electrical and Electronics Engineers, 2024. p. 1-8. ISBN: 979-8-3503-0836-5. Detail
  • JAROŠ, J.; MAJER, M.; HORKÝ, J.; VÁVRA, J. Web-Based Simulator of Superscalar RISC-V Processors. Atlanta, GA: 2024. p. 1-2. Detail
  • JAROŠ, J.; MAJER, M.; HORKÝ, J.; VÁVRA, J. Web-Based Simulator of Superscalar RISC-V Processors. In Proceedings of SC 2024-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis. Atlanta, GA: Institute of Electrical and Electronics Engineers, 2024. p. 1676-1684. ISBN: 979-8-3503-5554-3. Detail
  • JAROŠ, J.; TREEBY, B.; JAROŠ, M. k-Plan: From the Hospital to the Cluster and Back. Sydney: 2024. p. 0-0. Detail
  • JAROŠ, M.; JAROŠ, J. k-Dispatch: Enabling Cost-Optimized Biomedical Workflow Offloading. Solan: 2024. p. 0-0. Detail
  • JAROŠ, M.; JAROŠ, J. k-Dispatch: Enabling Cost-Optimized Biomedical Workflow Offloading. In HPDC '24: Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing. New York: Association for Computing Machinery, 2024. p. 358-360. ISBN: 979-8-4007-0413-0. Detail
  • JAWED, S.; FAYE, I.; MALIK, A. Deep learning-based assessment model for Real-time identification of visual learners using Raw EEG. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2024, vol. 32, no. 1, p. 378-390. ISSN: 1558-0210. Detail
  • KLHŮFEK, J.; ŠAFÁŘ, M.; MRÁZEK, V.; VAŠÍČEK, Z.; SEKANINA, L. Exploiting Quantization and Mapping Synergy in Hardware-Aware Deep Neural Network Accelerators. In 2024 27th International Symposium on Design & Diagnostics of Electronic Circuits & Systems (DDECS). Kielce: Institute of Electrical and Electronics Engineers, 2024. p. 1-6. ISBN: 979-8-3503-5934-3. Detail
  • KUNÍK, O.; JAROŠ, J. Accelerating Hybrid Local Domain Decomposition for the k-Wave Toolbox on Multi-GPU Systems. Ostrava: 2024. p. 0-0. Detail
  • LOJDA, J.; STRNADEL, J.; SMRŽ, P.; ŠIMEK, V. First Steps Towards Unified Low-Power IoT Design: The "DYNAMIC" Framework. 2024 IEEE East-West Design and Test Symposium, EWDTS 2024 - Proceedings. Yerevan: Institute of Electrical and Electronics Engineers, 2024. p. 1-6. ISBN: 979-8-3315-1576-8. Detail
  • LOJDA, J.; STRNADEL, J.; ŠIMEK, V.; SMRŽ, P.; HAYES, M.; POPP, R. The LoLiPoP-IoT Project: Long Life Power Platforms for Internet of Things. In Proceedings - 2024 27th Euromicro Conference on Digital System Design, DSD 2024. Paris: Institute of Electrical and Electronics Engineers, 2024. p. 604-611. ISBN: 979-8-3503-8038-5. Detail
  • MALIK, A.; HUSSAIN, M.; CHAUDHARY, S. Editorial: From assessment to intervention: role of consumer technology and neurotech in preventive mental health. Frontiers in Psychology. 2024. p. 1-3. ISSN: 1664-1078. Detail
  • MARTÍNEK, T.; KOŘENEK, J.; ČEJKA, T. LGBM2VHDL: Mapping of LightGBM Models to FPGA. In 2024 IEEE 32nd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). Orlando, FL: IEEE Computer Society, 2024. p. 97-103. ISBN: 979-8-3503-7243-4. Detail
  • MRÁZEK, V.; KOKKINIS, A.; PAPANIKOLAOU, P.; VAŠÍČEK, Z.; SIOZIOS, K.; TZIMPRAGOS, G.; TAHOORI, M.; ZERVAKIS, G. Evolutionary Approximation of Ternary Neurons for On-sensor Printed Neural Networks. 2024 IEEE/ACM International Conference on Computer Aided Design (ICCAD). New Jersey: 2024. Detail
  • OLŠÁK, O.; JAROŠ, J. Investigating the Possibility of Using Pruned FFT in Ultrasound Wave Propagation Simulations. Ostrava: 2024. p. 0-0. Detail
  • OLŠÁK, O.; JAROŠ, J. On the usage of the Sparse Fourier Transform in ultrasound propagation simulation. In ICBRA '23: Proceedings of the 10th International Conference on Bioinformatics Research and Applications. New York: Association for Computing Machinery, 2024. p. 107-113. ISBN: 979-8-4007-0815-2. Detail
  • OLŠÁK, O.; JAROŠ, J. Techniques for Efficient Fourier Transform Computation in Ultrasound Simulations. In HPDC '24: Proceedings of the 33nd International Symposium on High-Performance Parallel and Distributed Computing. New York: Association for Computing Machinery, 2024. p. 361-363. ISBN: 979-8-4007-0413-0. Detail
  • PIŇOS, M.; SEKANINA, L.; MRÁZEK, V. ApproxDARTS: Differentiable Neural Architecture Search with Approximate Multipliers. In 2024 The International Joint Conference on Neural Networks (IJCNN). Yokohama: Institute of Electrical and Electronics Engineers, 2024. p. 1-8. ISBN: 979-8-3503-5931-2. Detail
  • SEKANINA, L. Tutorial: Evolutionary Design Methods in Electronic Design Automation. In IEEE 42nd International Conference on Computer Design (ICCD). Milano: IEEE Computer Society, 2024. p. 689-690. ISBN: 979-8-3503-8040-8. Detail
  • STRNADEL, J.; LOJDA, J.; SMRŽ, P.; ŠIMEK, V. On SMC-Based Dependability Analysis in LoLiPoP-IoT Project. Steffen, B. (eds) Bridging the Gap Between AI and Reality (AISolA 2024). Lecture Notes in Computer Science. Limenas Hersonissou: Springer Nature Switzerland AG, 2024. p. 420-425. ISBN: 978-3-031-75434-0. ISSN: 0302-9743. Detail
  • STRNADEL, J.; LOJDA, J.; SMRŽ, P.; ŠIMEK, V. Machine Learning in Context of IoT/Edge Devices and LoLiPoP-IoT Project. In Proceedings of 32nd Austrian Workshop on Microelectronics (Austrochip 2024). Vienna: Institute of Electrical and Electronics Engineers, US, 2024. p. 1-4. ISBN: 979-8-3315-1617-8. Detail
  • ŠÍMA, J.; VIDNEROVÁ, P.; MRÁZEK, V. Energy Complexity of Convolutional Neural Networks. NEURAL COMPUTATION, 2024, vol. 36, no. 8, p. 1601-1625. ISSN: 0899-7667. Detail
  • VAŠÍČEK, Z. Automated Synthesis of Commutative Approximate Arithmetic Operators. In 2024 IEEE Congress on Evolutionary Computation, CEC 2024 - Proceedings. Yokohama: IEEE Computer Society, 2024. p. 1-8. ISBN: 979-8-3503-0836-5. Detail
  • VAŠÍČEK, Z.; MRÁZEK, V.; SEKANINA, L. Automated Verifiability-Driven Design of Approximate Circuits: Exploiting Error Analysis. In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE). Valencia: Institute of Electrical and Electronics Engineers, 2024. p. 1-6. ISBN: 979-8-3503-4859-0. Detail
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