Xu Yang

Orcid: 0000-0001-5944-2987

Affiliations:
  • Chinese Academy of Sciences, Institute of Semiconductors, State Key Laboratory of Superlattices and Microstructures, Beijing, China


According to our database1, Xu Yang authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
A 64 × 128 3D-Stacked SPAD Image Sensor for Low-Light Imaging.
Sensors, July, 2024

A Bio-Inspired Spiking Vision Chip Based on SPAD Imaging and Direct Spike Computing for Versatile Edge Vision.
IEEE J. Solid State Circuits, June, 2024

A Real-Time 2D/3D Perception Visual Vector Processor for 1920 × 1080 High-Resolution High-Speed Intelligent Vision Chips.
IEEE Trans. Circuits Syst. I Regul. Pap., February, 2024

DT-SCNN: dual-threshold spiking convolutional neural network with fewer operations and memory access for edge applications.
Frontiers Comput. Neurosci., 2024

2023
A 24.3 μJ/Image SNN Accelerator for DVS-Gesture With WS-LOS Dataflow and Sparse Methods.
IEEE Trans. Circuits Syst. II Express Briefs, November, 2023

A 128×128 15µm-Pitch DROIC with Pixel-Level 14-Bit ADC.
Proceedings of the IEEE International Conference on Integrated Circuits, 2023

A Lightweight Integer-STBP On-Chip Learning Method of Spiking Neural Networks For Edge Processors.
Proceedings of the IEEE International Conference on Integrated Circuits, 2023

2022
A 1000 fps Spiking Neural Network Tracking Algorithm for On-Chip Processing of Dynamic Vision Sensor Data.
Proceedings of the 2022 IEEE International Conference on Integrated Circuits, 2022

2020
TBC-Net: A real-time detector for infrared small target detection using semantic constraint.
CoRR, 2020

Deterministic conversion rule for CNNs to efficient spiking convolutional neural networks.
Sci. China Inf. Sci., 2020

2019
Efficient Reservoir Encoding Method for Near-Sensor Classification with Rate-Coding Based Spiking Convolutional Neural Networks.
Proceedings of the Advances in Neural Networks - ISNN 2019, 2019


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