Sep 2026· Science China Information Sciences· Vol 69· 0 citations· 56 references
TL;DR
Experiments show event-triggered visual neuron outputs resist deep learning-based privacy attacks, and develop a neuromorphic pose estimation framework based on event-triggered visual neuron output, achieving keypoint recognition accuracy comparable to conventional frame-based methods while significantly reducing power consumption and data bandwidth requirements.
Human vision achieves strong perception by performing probabilistic inference directly at the sensory level, integrating noise, prior knowledge and confidence in a unified process. Modern vision systems, however, remain dominated by camera‐centric, deterministic architectures that are energy‐intensive, latency‐limited...
Bio-inspired visual systems, owing to their event-driven operation, rapid response, and low-power processing capabilities, have emerged as promising candidates for next-generation efficient visual processing architectures. However, existing bio-inspired visual systems frequently employ rate coding, which necessitates a...
Bo-Hao Jin, Fu-Di Wang, Ai Chen et al.· IEEE Electron Device Letters· 0 citations
The asynchronous and sparse event streams output by event cameras pose a significant challenge to traditional computing architectures, whereas physical reservoir computing (RC) systems based on optoelectronic memristors offer an effective solution for realizing efficient in-sensor computing vision architectures. In t...
Qiu-Ting Ma, Kai Ma, Lu-Yao Ma et al.· ACS Photonics· 0 citations
A spectrally partitioned PbS/PEDOT:PSS/VOx all-optical memristor enables wavelength-selective potentiation and depression through regulated interfacial carrier dynamics. Highly linear bidirectional weight updates with a linearity of 0.9994, 8-bit conductance resolution, and an electrical energy consumption of 0.63 fJ p...
Jun-Chao Zhang, Bai Sun, Song-Ling Wang et al.· Nano-Micro Letters· 1 citation
Event-based sensors offer high temporal resolution, high dynamic range and low latency, making them wellsuited for wavefront sensing under high-speed turbulence. Recent work has demonstrated the effectiveness of event-based Shack–Hartmann wavefront sensing; however, many current methods rely on conventional framebased...
Divya Koganti, Matthew R. Ziemann, Christopher A. Metzler· Unconventional Imaging, Sens...· 0 citations
Always‐on acoustic recognition is becoming essential for intelligent vehicles, robotics, and embedded sensor nodes, yet conventional audio pipelines remain energy‐intensive because they rely on continuous sampling, digital feature extraction, and computation of heavy inference. Materials that encode temporal sound fe...