Ultrathin Gallium Nitride Quantum‑Disk‑in‑Nanowire‑Enabled Reconfigurable Bioinspired Sensor for High‑Accuracy Human Action Recognition

Ultrathin Gallium Nitride Quantum‑Disk‑in‑Nanowire‑Enabled Reconfigurable Bioinspired Sensor for High‑Accuracy Human Action Recognition
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Springer Nature Singapore
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Ultrathin Gallium Nitride Quantum-Disk-in-Nanowire-Enabled Reconfigurable Bioinspired Sensor for High-Accuracy Human Action Recognition - Nano-Micro Letters

Human action recognition (HAR) is crucial for the development of efficient computer vision, where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces. However, the absence of interactions among versatile biomimicking functionalities within a single device, which was developed for specific vision tasks, restricts the computational capacity, practicality, and scalability of in-sensor vision computing. Here, we propose a bioinspired vision sensor composed of a GaN/AlN-based ultrathin quantum-disks-in-nanowires (QD-NWs) array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing. By simply tuning the applied bias voltage on each QD-NW-array-based pixel, we achieve two biosimilar photoresponse characteristics with slow and fast reactions to light stimuli that enhance the in-sensor image quality and HAR efficiency, respectively. Strikingly, the interplay and synergistic interaction of the two photoresponse modes within a single device markedly increased the HAR recognition accuracy from 51.4% to 81.4% owing to the integrated artificial vision system. The demonstration of an intelligent vision sensor offers a promising device platform for the development of highly efficient HAR systems and future smart optoelectronics.

As artificial vision systems evolve, bridging the gap between sensing and processing remains a key challenge. Now, researchers from the University of Science and Technology of China, led by Prof. Yong Yan and Prof. Haiding Sun, have developed a reconfigurable bioinspired vision sensor using GaN/AlN quantum-disk-in-nanowires (QD-NWs) that emulates the human retina’s dual-cell system—delivering in-sensor computing for high-accuracy human action recognition (HAR).

Why This Bioinspired Sensor Matters

  • Dual-Mode Operation: Mimics Parvo cells (slow, high-contrast vision) and Magno cells (fast, motion-sensitive vision) via voltage-tunable persistent photocurrent (PPC).
  • In-Sensor Computing: Combines image enhancement and reservoir computing in a single device, reducing latency and power consumption.
  • High Accuracy: Boosts HAR accuracy from 51.4% to 81.4% through synergistic integration of both photoresponse modes.

Innovative Design and Features

  • Quantum-Confined Stark Effect (QCSE): Enables bias-tunable control over carrier recombination, switching between long-term and short-term PPC.
  • Nanowire Architecture: Ultrathin GaN/AlN QD-NWs grown on Si substrates offer CMOS compatibility, strain relaxation, and strong optoelectronic tunability.
  • Reservoir Computing System: Uses short-term PPC for temporal feature extraction and long-term PPC for image denoising and enhancement.

Applications and Performance

  • Image Enhancement: Under negative bias, the sensor enhances image contrast in real time—improving SNR from 1/0.3 to 1/0.15 without external processing.
  • Human Action Recognition: Under positive bias, the sensor acts as a hardware-based reservoir, classifying 10 human actions from the Weizmann dataset with >95% accuracy.
  • Robustness: Maintains >90% recognition accuracy even under 50% device noise, outperforming software-only approaches.

Conclusion and Outlook

This work introduces a compact, intelligent vision sensor that unites biological inspiration with semiconductor engineering, enabling real-time, low-power, high-accuracy visual perception. The QD-NW platform opens new pathways for neuromorphic vision systems, edge AI, and smart surveillance applications.

Stay tuned for more breakthroughs from Prof. Yong Yan and Prof. Haiding Sun’s team at USTC!

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Bioinspired Materials
Physical Sciences > Materials Science > Soft Materials > Bioinspired Materials
Sensors and Biosensors
Physical Sciences > Materials Science > Materials for Devices > Sensors and Biosensors
Artificial Intelligence
Mathematics and Computing > Computer Science > Artificial Intelligence
  • Nano-Micro Letters Nano-Micro Letters

    Nano-Micro Letters is a peer-reviewed, international, interdisciplinary and open-access journal that focus on science, experiments, engineering, technologies and applications of nano- or microscale structure and system in physics, chemistry, biology, material science, and pharmacy.