C. Posch
Researcher / author (OpenAlex)
Facts
2 properties- Affiliation
- Laboratoire de Recherche sur la Croissance Cellulaire, la Réparation et la Régénération Tissulairesas of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
- ORCID iD
- 0000-0002-0373-2739
- OpenAlex ID
- A5043840260as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
📚 Sources · 1
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 10
5.10 A 1280×720 Back-Illuminated Stacked Temporal Contrast Event-Based Vision Sensor with 4.86µm Pixels, 1.066GEPS Readout, Programmable Event-Rate Controller and Compressive Data-Formatting Pipeline,
Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor,
Giving machines humanlike eyes,
HFirst: A Temporal Approach to Object Recognition,
HUGNet: Hemi-Spherical Update Graph Neural Network applied to low-latency event-based optical flow,
Improving the Classification Accuracy in Label-Free Flow Cytometry Using Event-Based Vision and Simple Logistic Regression,
Predicting industrial‐scale cell culture seed trains–A Bayesian framework for model fitting and parameter estimation, dealing with uncertainty in measurements and model parameters, applied to a nonlinear kinetic cell culture model, using an MCMC method,
Real-time event-driven spiking neural network object recognition on the SpiNNaker platform
+2 more
← Authored by 10
5.10 A 1280×720 Back-Illuminated Stacked Temporal Contrast Event-Based Vision Sensor with 4.86µm Pixels, 1.066GEPS Readout, Programmable Event-Rate Controller and Compressive Data-Formatting Pipeline,
Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor,
Giving machines humanlike eyes,
HFirst: A Temporal Approach to Object Recognition,
HUGNet: Hemi-Spherical Update Graph Neural Network applied to low-latency event-based optical flow,
Improving the Classification Accuracy in Label-Free Flow Cytometry Using Event-Based Vision and Simple Logistic Regression,
Predicting industrial‐scale cell culture seed trains–A Bayesian framework for model fitting and parameter estimation, dealing with uncertainty in measurements and model parameters, applied to a nonlinear kinetic cell culture model, using an MCMC method,
Real-time event-driven spiking neural network object recognition on the SpiNNaker platform
+2 more
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0 sources
Summary
C. Posch is a human[1].