Qing Qin

According to our database1, Qing Qin authored at least 11 papers between 2018 and 2024.

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

Timeline

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Links

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Bibliography

2024
Interaction and manipulation for non-autonomous bright soliton solution of the coupled derivative nonlinear Schrödinger equations with Riemann-Hilbert method.
Appl. Math. Lett., March, 2024

2023
A Three-Wafer-Stacked Hybrid 15-MPixel CIS + 1-MPixel EVS With 4.6-GEvent/s Readout, In-Pixel TDC, and On-Chip ISP and ESP Function.
IEEE J. Solid State Circuits, November, 2023

An integrating spherical fuzzy AHP and axiomatic design approach and its application in human-machine interface design evaluation.
Eng. Appl. Artif. Intell., 2023

A 3-Wafer-Stacked Hybrid 15MPixel CIS + 1 MPixel EVS with 4.6GEvent/s Readout, In-Pixel TDC and On-Chip ISP and ESP Function.
Proceedings of the IEEE International Solid- State Circuits Conference, 2023

2022
Research on laser welding pressure control system based on MAC-IBA.
Proceedings of the 7th International Conference on Cyber Security and Information Engineering, 2022

2020
Seizure Suppression in a Thalamocortical Computational Model of Absence Epilepsy by Linear Delayed Feedback Control.
Proceedings of the 13th International Congress on Image and Signal Processing, 2020

Epileptic Seizure Prediction from the Scalp EEG Signals by using Random Forest Algorithm.
Proceedings of the 13th International Congress on Image and Signal Processing, 2020

Effect of Degree Distribution on Signal Propagation Based on Heterogeneous High-frequency Stimuli in Feedforward Networks.
Proceedings of the BIBE 2020: The Fourth International Conference on Biological Information and Biomedical Engineering, 2020

2019
Power Analysis of EEG Data in Multiple Brain Regions during Fatigue Driving.
Proceedings of the 12th International Congress on Image and Signal Processing, 2019

Effects of Degree Distribution on Signal Propagation in the Heterogeneous Feedforward Neural Network.
Proceedings of the 12th International Congress on Image and Signal Processing, 2019

2018
To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference.
Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, 2018


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