Results 61 to 70 of about 3,555,912 (299)

Imaging from temporal data via spiking convolutional neural networks [PDF]

, 2020
A new approach for imaging that is solely based on the time of flight of photons coming from the entire imaged scene, combined with a novel machine learning algorithm for image reconstruction: a spiking convolutional neural network (SCNN) named Spike-SPI
Kapitany, Valentin, Turpin, Alex, Faccio, Daniele, Soraghan, John, Lyons, Ashley, Kirkland, Paul, Di Caterina, Gaetano   +6 more
core   +1 more source

Evolving Spiking Neural Networks with NEAT [PDF]

, 2020
Spiking neural networks (SNNs) attempt to computationally model biological neurons. While similar to artificial neural networks (ANNs), SNNs preserve the temporal and binary aspects of neurons.
Hirsch, Mary
core  

Independent component analysis in spiking neurons [PDF]

, 2010
Although models based on independent component analysis (ICA) have been successful in explaining various properties of sensory coding in the cortex, it remains unclear how networks of spiking neurons using realistic plasticity rules can realize such ...
Cristina Savin, Savin Cristina, Triesch, Jochen, Jochen Triesch, Joshi Prashant, Triesch Jochen, Prashant Joshi, Joshi, Prashant, Savin, Cristina   +8 more
core   +2 more sources

An exact mapping from ReLU networks to spiking neural networks

, 2023
Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence. However, training deep SNNs from scratch or converting deep artificial neural networks to SNNs without loss of performance has been a challenge.
Wulfram Gerstner, Ana Stanojevic, Cherubini, Giovanni, Stanisław Woźniak, Bellec, Guillaume, Pantazi, Angeliki, Angeliki Pantazi, Giovanni Cherubini, Woźniak, Stanisław, Guillaume Bellec, Gerstner, Wulfram, Stanojevic, Ana   +11 more
core   +1 more source

PlaNeural: Spiking Neural Networks that Plan [PDF]

Procedia Computer Science, 2016
PlaNeural is a spike-based neural network that has the ability to plan. The network is a spreading activation network implemented with Cell Assemblies; this combination has built a dynamic network of nodes that is able to interact with an environment and respond appropriately.
Ian Mitchell 0002, Christian R. Huyck, Carl Evans   +2 more
openaire   +1 more source

Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons [PDF]

, 2008
Neftci E, Chicca E, Indiveri G, Slotine J-J, Douglas R. Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons. Presented at the Advances in Neural Information Processing Systems 20 (NIPS), Vancouver, British Columbia ...
Douglas, R., Indiveri, G., Koller, D., Chicca, Elisabetta ; https://orcid.org/, Slotine, J.-J., Singer, Y., Roweis, S., Neftci, E., Platt, J.C.   +8 more
core  

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA

FEBS Open Bio, EarlyView.
Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley   +1 more source

Modeling Spiking Neural Networks on SpiNNaker [PDF]

Computing in Science & Engineering, 2010
SpiNNaker is a massively parallel architecture with more than a million processing cores that can model up to 1 billion spiking neurons in biological real time. © 2006 IEEE.
Jin, Xin, Luján, Mikel, Plana, Luis A., Davies, Sergio, Temple, Steve, Furber, Steve B.   +5 more
openaire   +2 more sources

Exploring olfactory sensory networks: Simulations and hardware emulation [PDF]

, 2010
Olfactory stimuli are represented in a highdimensional space by neural networks of the olfactory system. A great deal of research in olfaction has focused on this representation within the first processing stage, the olfactory bulb (vertebrates) or ...
Beyeler, Michael, Galizia, G, Fabio Stefanini, Henning Proske, Beyeler, M., Chicca, Elisabetta, Proske, H., Giovanni Galizia, Beyeler, M, Michael Beyeler, Chicca, E, Galizia, C. Giovanni, Stefanini, F., Proske, Henning, Proske, H, Elisabetta Chicca, Galizia, G., Stefanini, Fabio, Chicca, Elisabetta ; https://orcid.org/, Stefanini, F   +19 more
core   +1 more source