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Neuromorphic In-Memory Computing for Marine Visual-Auditory Perception
Qunrui Deng1, Wenjie Chen1, Xueting Liu1
1Guangdong Provincial Key Laboratory of Chip and Integration Technology, School of Electronic Science and Engineering (School of Microelectronics), South China Normal University, Foshan, P. R. China.
Advanced Materials (Deerfield Beach, Fla.)
|June 29, 2026
Summary
We developed a novel neuromorphic transistor for underwater perception. This device enables efficient, real-time processing of visual and auditory signals, improving deep-sea exploration capabilities.
Area of Science:
- Neuroscience
- Materials Science
- Oceanography
Background:
- Deep-sea exploration is vital but hindered by bulky, high-latency sensor systems.
- Current underwater perception systems struggle with real-time data processing due to extreme conditions and segregated signal pathways.
Purpose of the Study:
- To develop an integrated, low-power, and compact hardware solution for intelligent underwater perception.
- To create a neuromorphic transistor capable of in-memory dual-mode processing of visual and auditory signals.
Main Methods:
- Developed a neuromorphic floating-gate transistor (NFT) with integrated electrical and optical memory functionalities.
- Employed the NFT for in-memory processing of sonar echo data using a convolutional neural network (CNN) for seafloor classification.
- Utilized the NFT's optical properties for marine biological image recognition, incorporating green-light window optimization.
Main Results:
- The NFT demonstrated rapid switching (∼14 µs), high on/off ratio (10^6), and excellent endurance (>10^4 cycles).
- Achieved 88% accuracy in seafloor mineral and rock classification via sonar processing.
- Realized 80% accuracy in marine biological image recognition using optical processing and green-light enhancement.
Conclusions:
- The synergistic electro-optical in-memory computing architecture offers an efficient, low-power solution for underwater intelligent perception.
- The developed neuromorphic transistor overcomes limitations of current sensor technologies for deep-sea applications.
- This technology paves the way for advanced real-time intelligent systems in challenging marine environments.
Keywords:
electro‐optical synapsein‐memory computingneuromorphic floating‐gate transistornon‐volatile memoryMore Related Videos
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