ReviewFrontiers in neural circuits2021
Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review.
Review in Frontiers in neural circuits, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Morphologically tunable mycelium chips for physical reservoir computing.Scientific reports · 2026Article
- Covariant spatio-temporal receptive fields for spiking neural networks.Nature communications · 2025Article
- Resampling Multi-Resolution Signals Using the Bag of Functions Framework: Addressing Variable Sampling Rates in Time Series Data.Sensors (Basel, Switzerland) · 2025Article
- Signal-to-event encoding parameter selection for multiple event classification with spiking neural networks.Frontiers in neuroscience · 2025Article
- Neuromorphic engineering: Artificial brains for artificial intelligence.Annals of the New York Academy of Sciences · 2024Article
- Model-agnostic neural mean field with a data-driven transfer function.Neuromorphic computing and engineering · 2024Article
- Model-Agnostic Neural Mean Field With The Refractory SoftPlus Transfer Function.bioRxiv : the preprint server for biology · 2024Article
- Bioinspired Perception and Navigation of Service Robots in Indoor Environments: A Review.Biomimetics (Basel, Switzerland) · 2023Review
- Editorial: Focus on methods: neural algorithms for bio-inspired robotics.Frontiers in neurorobotics · 2023Article
- Integration of neuromorphic AI in event-driven distributed digitized systems: Concepts and research directions.Frontiers in neuroscience · 2023Article
- Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The nervous systems converts the physical quantities sensed by its primary receptors into trains of events that are then processed in the brain. The unmatched efficiency in information processing has long inspired engineers to seek brain-like approaches to sensing and signal processing. The key principle pursued in neuromorphic sensing is to shed the traditional approach of periodic sampling in favor of an event-driven scheme that mimicks sampling as it occurs in the nervous system, where events are preferably emitted upon the change of the sensed stimulus. In this paper we highlight the advantages and challenges of event-based sensing and signal processing in the visual, auditory and olfactory domains. We also provide a survey of the literature covering neuromorphic sensing and signal processing in all three modalities. Our aim is to facilitate research in event-based sensing and signal processing by providing a comprehensive overview of the research performed previously as well as highlighting conceptual advantages, current progress and future challenges in the field.
Indexed as
Identifiers
What OpenQuestion holds
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.