A new artificial synapse, controlled entirely by light, enables in-sensor neuromorphic processing for more efficient and noise-resistant imaging systems.
Key Details
- 1Researchers engineered a synaptic device using a rare-earth-doped crystal with persistent optical afterglow.
- 2The synapse uses light for both input and state update, avoiding electrical signals and reducing energy demands.
- 3It mimics neural plasticity, showing both signal enhancement (UV facilitates) and suppression (near-infrared depresses).
- 4Integration with a silicon imaging sensor led to a neuromorphic camera prototype capable of in-sensor contrast enhancement and denoising.
- 5Neural networks using this optical synapse achieved nearly 96% accuracy in digit recognition, vs. 78% without the technique.
Why It Matters
By combining sensing, memory, and processing using optical signals, this approach points towards future imaging systems—potentially relevant to clinical imaging and radiology AI—that are faster, more power-efficient, and intrinsically robust to noise.
Source
EurekAlert
Related News
•EurekAlert
AI-Simulation Approach Achieves 90% Faster Brain MRI with Minimal Data
A simulation-based AI method can reconstruct brain MRI scans with only 10% of the usual data, greatly reducing scan times.
•EurekAlert
Mayo Clinic Showcases Imaging AI and Early Cancer Detection Advances at ASCO 2026
Mayo Clinic researchers will present over 30 studies at ASCO 2026, highlighting new advances in imaging AI, data science, and early cancer detection.
•EurekAlert
ACM Honors 3D Generative AI and NeRF Innovators With Technical Awards
ACM recognized researchers for breakthroughs in wireless standards, artificial intelligence, and 3D generative AI, including major advances in neural radiance fields impacting computer vision and medical imaging.