Muqing Li

According to our database1, Muqing Li authored at least 16 papers between 2014 and 2024.

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

Timeline

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Links

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Bibliography

2024
High Efficiency Inference Accelerating Algorithm for NOMA-Based Edge Intelligence.
IEEE Trans. Wirel. Commun., November, 2024

E-commerce Webpage Recommendation Scheme Base on Semantic Mining and Neural Networks.
CoRR, 2024

Application of Multimodal Fusion Deep Learning Model in Disease Recognition.
CoRR, 2024

Research on Disease Prediction Model Construction Based on Computer AI deep Learning Technology.
CoRR, 2024

Application of Computer Deep Learning Model in Diagnosis of Pulmonary Nodules.
CoRR, 2024

Exploration of Attention Mechanism-Enhanced Deep Learning Models in the Mining of Medical Textual Data.
CoRR, 2024

2023
High Efficiency Inference Accelerating Algorithm for NOMA-based Mobile Edge Computing.
CoRR, 2023

Does informativity modulate linearization preferences in reference production?
Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

Adaptive Hierarchy-Branch Fusion for Online Knowledge Distillation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2019
An Efficient Extended Targets Detection Framework Based on Sampling and Spatio-Temporal Detection.
Sensors, 2019

Adaptive Segmentation of Remote Sensing Images Based on Global Spatial Information.
Sensors, 2019

Intelligent design and implementation of blockchain and Internet of things-based traffic system.
Int. J. Distributed Sens. Networks, 2019

Improved multilevel thresholding plot fusion method using the rain algorithm for the detection of closely extended targets.
IET Signal Process., 2019

An improved partitioning algorithm based on FCM algorithm for extended target tracking in PHD filter.
Digit. Signal Process., 2019

2017
Track-before-detect algorithm based on dynamic programming for multi-extended-targets detection.
IET Signal Process., 2017

2014
Subpopulation Diversity Based Setting Success Rate of Migration for Distributed Evolutionary Algorithms.
Proceedings of the PRICAI 2014: Trends in Artificial Intelligence, 2014


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