Browsing by Author "Hafner, Verena Vanessa"

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    • Proceedings of Abstracts Engineering and Computer Science Research Conference 2019 

      Nwawe, Richard; Grasso, Marzio; CHEN, Yong Kang; Klusak, Jan; Rosiello, Vincenzo; Counsell, Nathan; Herfatmanesh, Mohammad Reza; Partou, Helen; Menon, Catherine; Barker, Trevor; Veneziano, Vito; Kirner, Raimund; Tveretina, Olga; Verma, Alok; Lane, Peter; Lilley, Mariana; Canoville, Paul; Robinson, Matthew; Crook, Brian; Hall, Samantha; Kaye, Richard; Johnston, Ian; McCluskey, Daniel; Tracey, Mark; Munro, Ian; Wang, Yuan; Suckow, Bjorn; Klaholz, Ingo; Drix, Damien; Hafner, Verena Vanessa; Schmuker, Michael; Sinha, Ankur; Metzner, Christoph; Davey, Neil; Adams, Roderick; Steuber, Volker; Miko, Rebecca; Toffe, Gilles; Ren, Guogang; Montalvão, Diogo; Ismail, Sikiru O.; Newman, James; Dhakal, Hom; Sunmola, Funlade; Panday, Deepak; Helian, Na; Amafabia, Daerefa-a; David-West, Opukuro; Haritos, George; Schirmer, Pascal; Mporas, Iosif; Skaltsas, Grigorios; Siadati, Rana; Wernick, Paul; Sutton, Samuel; Lekkala, Himayasri Rao; Sayers, Paul; Khan, Imran; Cañamero, Lola; Hassan, Eheda; Denai, Mouloud; Pissanidis, Georgios; Goncharenko, Julia; Schilstra, Maria; Beka, Nathan; te Boekhorst, Rene; Bonivart, Agnes; Nehaniv, Chrystopher; Kadir, Shabnam; Bhavsar, Ronakben; Sun, Yi; Mayor, David; Steffert, Tony; CHEN, Yong Kang; Chrysanthou, Andreas; Johnston, Ian; Kirner, Raimund; Kourtessis, Pandelis; McCluskey, Daniel; Polani, Daniel; Steuber, Volker; Sun, Yichuang (University of Hertfordshire, 2019-09-01)
      This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This ...

    • Sparse Coding with a Somato-Dendritic Rule 

      Drix, Damien; Hafner, Verena Vanessa; Schmuker, Michael (2020-06-26)
      Cortical neurons are silent most of the time. This sparse activity is energy efficient, and the resulting neural code has favourable properties for associative learning. Most neural models of sparse coding use some form ...