ArticleFrontiers in neuroscience2015
Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades.
Article in Frontiers in neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers.
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Who cites it
110 citing papers in PubMed.
- Temporal coding enables hyperacuity in event-based vision.Nature communications · 2026Article
- WSAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Programmable memtransistor array with temporal dynamics modulation for efficient time-series data processing.Nature communications · 2026Article
- Event-Based Vision at the Edge: A Review.Brain sciences · 2026Review
- PdNeuRAM: forming-free, multi-bit Pd/HfOCommunications engineering · 2026Article
- Backpropagation-free spiking neural networks with the forward-forward algorithm.Scientific reports · 2026Article
- Characterization of a Spiking Convolutional Processor for FPGA.Sensors (Basel, Switzerland) · 2026Article
- Article
- Eye Movement Classification Using Neuromorphic Vision Sensors.Journal of eye movement research · 2026Article
- Model-agnostic linear-memory online learning in spiking neural networks.Nature communications · 2026Article
- A compressed sensing neuromorphic processor for sparse signal classification.Frontiers in neuroscience · 2026Article
- Distributed implantable microchips as wireless networks for neural sensing and stimulation.Frontiers in neuroscience · 2026Review
- Operational manifolds in spiking neural networks.Frontiers in neuroscience · 2026Article
- Hybrid GNN-LSTM defense with differential privacy and secure multi-party computation for edge-optimized neuromorphic autonomous systems.Scientific reports · 2025Article
- Three-factor learning in spiking neural networks: An overview of methods and trends from a machine learning perspective.Patterns (New York, N.Y.) · 2025Review
- Hardware, Algorithms, and Applications of the Neuromorphic Vision Sensor: A Review.Sensors (Basel, Switzerland) · 2025Review
- Predictive Coding Light.Nature communications · 2025Article
- Design and Experimental Validation of Pipeline Defect Detection in Low-Illumination Environments Based on Bionic Visual Perception.Biomimetics (Basel, Switzerland) · 2025Article
- Topology optimization of random memristors for input-aware dynamic SNN.Science advances · 2025Article
- The neurobench framework for benchmarking neuromorphic computing algorithms and systems.Nature communications · 2025Review
50 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labeling existing data. The task is further complicated by a desire to simultaneously provide traditional frame-based recordings to allow for direct comparison with traditional Computer Vision algorithms. Here we propose a method for converting existing Computer Vision static image datasets into Neuromorphic Vision datasets using an actuated pan-tilt camera platform. Moving the sensor rather than the scene or image is a more biologically realistic approach to sensing and eliminates timing artifacts introduced by monitor updates when simulating motion on a computer monitor. We present conversion of two popular image datasets (MNIST and Caltech101) which have played important roles in the development of Computer Vision, and we provide performance metrics on these datasets using spike-based recognition algorithms. This work contributes datasets for future use in the field, as well as results from spike-based algorithms against which future works can compare. Furthermore, by converting datasets already popular in Computer Vision, we enable more direct comparison with frame-based approaches.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.