An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data
Authors
Keywords
-
Journal
Frontiers in Neuroscience
Volume 11, Issue -, Pages -
Publisher
Frontiers Media SA
Online
2017-06-28
DOI
10.3389/fnins.2017.00350
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition
- (2017) Xavier Lagorce et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Skimming Digits: Neuromorphic Classification of Spike-Encoded Images
- (2016) Gregory K. Cohen et al. Frontiers in Neuroscience
- Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation
- (2016) Qian Liu et al. Frontiers in Neuroscience
- Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines
- (2016) Emre O. Neftci et al. Frontiers in Neuroscience
- Training Deep Spiking Neural Networks Using Backpropagation
- (2016) Jun Haeng Lee et al. Frontiers in Neuroscience
- HFirst: A Temporal Approach to Object Recognition
- (2015) Garrick Orchard et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Online and adaptive pseudoinverse solutions for ELM weights
- (2015) André van Schaik et al. NEUROCOMPUTING
- Unsupervised learning of digit recognition using spike-timing-dependent plasticity
- (2015) Peter U. Diehl et al. Frontiers in Computational Neuroscience
- Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms
- (2015) Evangelos Stromatias et al. Frontiers in Neuroscience
- Event-driven contrastive divergence: neural sampling foundations
- (2015) Emre Neftci et al. Frontiers in Neuroscience
- Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades
- (2015) Garrick Orchard et al. Frontiers in Neuroscience
- Poker-DVS and MNIST-DVS. Their History, How They Were Made, and Other Details
- (2015) Teresa Serrano-Gotarredona et al. Frontiers in Neuroscience
- Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator
- (2014) Daniel Neil et al. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
- Retinomorphic Event-Based Vision Sensors: Bioinspired Cameras With Spiking Output
- (2014) Christoph Posch et al. PROCEEDINGS OF THE IEEE
- The SpiNNaker Project
- (2014) Steve B. Furber et al. PROCEEDINGS OF THE IEEE
- A million spiking-neuron integrated circuit with a scalable communication network and interface
- (2014) P. A. Merolla et al. SCIENCE
- Event-driven contrastive divergence for spiking neuromorphic systems
- (2014) Emre Neftci et al. Frontiers in Neuroscience
- A 128$\,\times$128 1.5% Contrast Sensitivity 0.9% FPN 3 µs Latency 4 mW Asynchronous Frame-Free Dynamic Vision Sensor Using Transimpedance Preamplifiers
- (2013) Teresa Serrano-Gotarredona et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
- Immunity to Device Variations in a Spiking Neural Network With Memristive Nanodevices
- (2013) Damien Querlioz et al. IEEE TRANSACTIONS ON NANOTECHNOLOGY
- Mapping from Frame-Driven to Frame-Free Event-Driven Vision Systems by Low-Rate Rate Coding and Coincidence Processing--Application to Feedforward ConvNets
- (2013) J. A. Perez-Carrasco et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Real-time classification and sensor fusion with a spiking deep belief network
- (2013) Peter O'Connor et al. Frontiers in Neuroscience
- Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity
- (2012) Olivier Bichler et al. NEURAL NETWORKS
- A Large-Scale Model of the Functioning Brain
- (2012) C. Eliasmith et al. SCIENCE
- A 3.6 $\mu$s Latency Asynchronous Frame-Free Event-Driven Dynamic-Vision-Sensor
- (2011) Juan Antonio Lenero-Bardallo et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
- An Event-Driven Multi-Kernel Convolution Processor Module for Event-Driven Vision Sensors
- (2011) Luis Camunas-Mesa et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
- A QVGA 143 dB Dynamic Range Frame-Free PWM Image Sensor With Lossless Pixel-Level Video Compression and Time-Domain CDS
- (2010) Christoph Posch et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
- A 32$\,\times\,$32 Pixel Convolution Processor Chip for Address Event Vision Sensors With 155 ns Event Latency and 20 Meps Throughput
- (2010) Luis Camunas-Mesa et al. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
- A 128$\times$128 120 dB 15 $\mu$s Latency Asynchronous Temporal Contrast Vision Sensor
- (2008) Patrick Lichtsteiner et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
- Cross-validation and bootstrapping are unreliable in small sample classification
- (2008) A. Isaksson et al. PATTERN RECOGNITION LETTERS
- Large-scale model of mammalian thalamocortical systems
- (2008) E. M. Izhikevich et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now