• Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches 

      Heiney, Kristine; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel; Nichele, Stefano (2019 IEEE Symposium Series on Computational Intelligence (SSCI);, Conference object, 2020)
      In this work, we report the preliminary analysis of the electrophysiological behavior of in vitro neuronal networks to identify when the networks are in a critical state based on the size distribution of network-wide ...
    • Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity 

      Jensen Farner, Jørgen; Weydahl, Håkon; Jahren, Ruben; Huse Ramstad, Ola; Nichele, Stefano; Heiney, Kristine Anne (IEEE Symposium Series on Computational Intelligence (SSCI);2021 IEEE Symposium Series on Computational Intelligence (SSCI), Conference object, 2021-01-24)
      Neuro-inspired models and systems have great potential for applications in unconventional computing. Often, the mechanisms of biological neurons are modeled or mimicked in simulated or physical systems in an attempt to ...
    • Performance of data enhancements and training optimization for neural network: A polyp detection case study 

      Henriksen, Fredrik Lund; Jensen, Rune; Stensland, Håkon Kvale; Johansen, Dag; Riegler, Michael; Halvorsen, Pål (IEEE International Symposium on Computer-Based Medical Systems; 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), Conference object, 2019)
      Deep learning using neural networks is becoming more and more popular. It is frequently used in areas like video analysis, image retrieval, traffic forecast and speech recognition. In this respect, the learning and training ...