Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation | Paper Citation Record

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This paper cites On the computational power of winner-take-all,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation On the computational power of winner-take-all,

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This paper cites Triplets of spikes in a model of spike timing-dependent plasticity,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Triplets of spikes in a model of spike timing-dependent plasticity,

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This paper cites The perceptron: a probabilistic model for information storage and organization in the brain.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation The perceptron: a probabilistic model for information storage and organization in the brain

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This paper cites Minsky and S.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Minsky and S

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Notice on the law that the population follows in its growth,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Rectified linear units improve restricted boltzmann machines,

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This paper cites Learning repre- sentations by back-propagating errors,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Learning repre- sentations by back-propagating errors,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Deep learning,

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This paper cites A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection,

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This paper cites Deep learning in spiking neural networks,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Deep learning in spiking neural networks,

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This paper cites Supervised learning in spiking neural networks with resume: sequence learning, classification, and spike shifting,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Supervised learning in spiking neural networks with resume: sequence learning, classification, and spike shifting,

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This paper cites Bp-stdp: Approximating backpropagation using spike timing dependent plasticity,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Bp-stdp: Approximating backpropagation using spike timing dependent plasticity,

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This paper cites Learning rules in spiking neural networks: A survey,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Learning rules in spiking neural networks: A survey,

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This paper cites A survey of supervised learning models for spiking neural network,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A survey of supervised learning models for spiking neural network,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A review of snn implementation on fpga,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Spiking neural networks hardware im- plementations and challenges: A survey,

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This paper cites Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities

Reference 17

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Observation f1e87835-c954-4ade-a308-1fc2c3a50e8a · outbound

This paper cites Research progress of spiking neural network in image classification: a review,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Research progress of spiking neural network in image classification: a review,

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This paper cites Evolving spiking neural network—a survey,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Evolving spiking neural network—a survey,

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This paper cites Evolving spiking neural network: a comprehensive survey of its variants and their results,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Evolving spiking neural network: a comprehensive survey of its variants and their results,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Training spiking neural networks using lessons from deep learning,

Reference 21

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This paper cites Preferred reporting items for systematic reviews and meta-analyses: the prisma statement,.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Preferred reporting items for systematic reviews and meta-analyses: the prisma statement,

Reference 22

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Deep spiking neural networks for large vocabulary automatic speech recognition,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Deep spiking neural network model for time-variant signals classification: a real-time speech recognition approach,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A survey of robotics control based on learning-inspired spiking neural networks,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Evolving spiking neural network controllers for autonomous robots,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Spiking neural network (snn) control of a flapping insect-scale robot,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A neuromorphic processing system with spike-driven snn processor for wearable ecg classification,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Neural coding in spiking neural networks: A comparative study for robust neuromorphic systems,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Rate coding or direct coding: Which one is better for accu- rate, robust, and energy-efficient spiking neural networks?

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Temporal pattern coding in deep spiking neural networks,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Skimming digits: neuromorphic classification of spike- encoded images,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Unsupervised learning of digit recognition using spike-timing-dependent plasticity,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Unsupervised learning of event-based image recordings using spike-timing-dependent plasticity,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation An event-driven categorization model for aer image sensors using multispike encoding and learning,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Scene context classification with event-driven spiking deep neural networks,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Hfirst: A temporal approach to object recogni- tion,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Deep spiking con- volutional neural network trained with unsupervised spike-timing- dependent plasticity,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Spiking deep convolutional neural networks for energy-efficient object recognition,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Simple framework for constructing functional spiking recurrent neural networks,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Long short-term memory spiking networks and their applications,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Effective and efficient compu- tation with multiple-timescale spiking recurrent neural networks,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Sparse deep belief net model for visual area v2,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Spiking convolutional deep belief networks,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Robustness of spiking deep belief networks to noise and reduced bit precision of neuro-inspired hardware platforms,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Spikeprop: backpropa- gation for networks of spiking neurons

Reference 49

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Fast modifications of the spikeprop algorithm,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Training deep spiking neural networks using backpropagation,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Unsupervised learning of visual fea- tures through spike timing dependent plasticity,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Con- version of continuous-valued deep networks to efficient event-driven networks for image classification,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Spiking Deep Networks with LIF Neurons

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Nengo: a python tool for building large-scale functional brain models,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Bindsnet: A machine learning-oriented spiking neural networks library in python,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip,

Reference 57

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 58

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Optimizing the energy consumption of spiking neural networks for neuromorphic applications,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Synaptic activity and hardware footprint of spiking neural networks in digital neuromorphic systems,

Reference 60

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Artificial intelligence and computer vision education: Codifying student learning gains and attitudes,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Which model to use for cortical spiking neurons?

Reference 62

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation The discovery of the action potential,

Reference 63

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Gerstner and W

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Synaptic vesicles and exocytosis,

Reference 65

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Presynaptic signaling by heterotrimeric g-proteins,

Reference 66

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Unresolved cited work

Reference 67

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Louis lapicque,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A quantitative description of membrane current and its application to conduction and excitation in nerve,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Dayan and L

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Event-snn-resources,

Reference 71

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A high-performance neuron for artificial neural network based on izhikevich model,

Reference 72

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation On the capabilities and computational costs of neuron models,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network,

Reference 74

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Event-driven spiking neural network based on membrane potential modulation for remote sensing image classification,

Reference 75

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing,

Reference 76

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation An event-driven classifier for spiking neural networks fed with synthetic or dynamic vision sensor data,

Reference 77

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Poisson model of spike generation,

Reference 78

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Stdp-based spiking deep convolutional neural networks for object recognition,

Reference 79

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A dynamic vision sensor with 1% temporal contrast sensitivity and in-pixel asynchronous delta modulator for event encoding,

Reference 80

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Temporal-coded deep spiking neural network with easy training and robust performance,

Reference 81

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Neural population coding for effective temporal classification,

Reference 82

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A 128x128 120db 15 µs latency asynchronous temporal contrast vision sensor,

Reference 83

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A qvga 143 db dynamic range frame-free pwm image sensor with lossless pixel-level video compression and time-domain cds,

Reference 84

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A 240 × 180 130 db 3 µs latency global shutter spatiotemporal vision sensor,

Reference 85

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation 4.1 a 640 × 480 dynamic vision sensor with a 9µm pixel and 300meps address-event representation,

Reference 86

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Event- based vision: A survey,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Microsaccade-inspired event camera for robotics,

Reference 88

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation The mnist database of handwritten digit images for machine learning research,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Unresolved cited work

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories,

Reference 91

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Learning multiple layers of features from tiny images,

Reference 92

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Imagenet: A large-scale hierarchical image database,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Converting static image datasets to spiking neuromorphic datasets using saccades,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A 128x128 1.5% contrast sensitivity 0.9% fpn 3 µs latency 4 mw asynchronous frame- free dynamic vision sensor using transimpedance preamplifiers,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Mapping from frame- driven to frame-free event-driven vision systems by low-rate rate- coding and coincidence processing. application to feed forward con- vnets,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Efficient feedforward categorization of objects and human postures with address-event image sensors,

Reference 97

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Neuromorphic benchmark datasets for pedestrian detection, action recognition, and fall detection,

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Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation Hats: Histograms of averaged time surfaces for robust event-based ob- ject classification,

Reference 99

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This paper cites A Large Scale Event-based Detection Dataset for Automotive.

Event-based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation A Large Scale Event-based Detection Dataset for Automotive

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