Zobrazeno 1 - 10
of 372
pro vyhledávání: '"Poirazi Panayiota"'
Autor:
Chavlis, Spyridon, Poirazi, Panayiota
Artificial neural networks (ANNs) are at the core of most Deep learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. However, unlike biological brains who tackl
Externí odkaz:
http://arxiv.org/abs/2404.03708
The brain is a remarkably capable and efficient system. It can process and store huge amounts of noisy and unstructured information using minimal energy. In contrast, current artificial intelligence (AI) systems require vast resources for training wh
Externí odkaz:
http://arxiv.org/abs/2306.08007
The brain is a highly efficient system evolved to achieve high performance with limited resources. We propose that dendrites make information processing and storage in the brain more efficient through the segregation of inputs and their conditional i
Externí odkaz:
http://arxiv.org/abs/2306.07101
Publikováno v:
BMC Neuroscience, Vol 12, Iss Suppl 1, p O7 (2011)
Externí odkaz:
https://doaj.org/article/6b8cbaba16404bdcb216a85c85d47fc8
Publikováno v:
BMC Neuroscience, Vol 10, Iss Suppl 1, p P42 (2009)
Externí odkaz:
https://doaj.org/article/b111e744755a475ba345382de473dae5
Current deep learning architectures show remarkable performance when trained in large-scale, controlled datasets. However, the predictive ability of these architectures significantly decreases when learning new classes incrementally. This is due to t
Externí odkaz:
http://arxiv.org/abs/2110.13611
Autor:
Chavlis, Spyridon, Poirazi, Panayiota
Publikováno v:
Current Opinion in Neurobiology 70 (2021): 1-10
This article highlights specific features of biological neurons and their dendritic trees, whose adoption may help advance artificial neural networks used in various machine learning applications. Advancements could take the form of increased computa
Externí odkaz:
http://arxiv.org/abs/2106.07490
Autor:
Poirazi Panayiota, Pavlidis Pavlos
Publikováno v:
BMC Bioinformatics, Vol 7, Iss 1, p 345 (2006)
Abstract Background Identification of molecular markers for the classification of microarray data is a challenging task. Despite the evident dissimilarity in various characteristics of biological samples belonging to the same category, most of the ma
Externí odkaz:
https://doaj.org/article/6ed522df83da4c6ea78a03f01795d3d7
Autor:
Tzilivaki, Alexandra, Tukker, John J., Maier, Nikolaus, Poirazi, Panayiota, Sammons, Rosanna P., Schmitz, Dietmar
Publikováno v:
In Neuron 18 October 2023 111(20):3154-3175
Autor:
Troullinou, Eirini, Tsagkatakis, Grigorios, Chavlis, Spyridon, Turi, Gergely, Li, Wen-Ke, Losonczy, Attila, Tsakalides, Panagiotis, Poirazi, Panayiota
Identification of different neuronal cell types is critical for understanding their contribution to brain functions. Yet, automated and reliable classification of neurons remains a challenge, primarily because of their biological complexity. Typical
Externí odkaz:
http://arxiv.org/abs/1911.09977