Maoguo Gong
Xidian University
506 Papers
1.4K Citations
Maoguo Gong is an academic researcher from Xidian University. The author has contributed to research in topics: Computer science & Evolutionary algorithm. The author has an hindex of 56, co-authored 377 publications. Previous affiliations of Maoguo Gong include Shandong University of Science and Technology & Chinese Ministry of Education.
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Papers
Fuzzy multi-objective sparse feature learning
Na Li,Yu Lei,Jiao Shi,Maoguo Gong +3 more
- 01 Jun 2017
TL;DR: This paper introduces fuzzy set theory to neural networks where the parameters are expressed by fuzzy numbers, and proposes a fuzzy multi-objective sparse feature learning (FMSFL) model, where a multi- objective optimization model is established, and reconstruction error and sparsity of fuzzy model are considered as two objectives.
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Nucleus Neural Network: A Data-driven Self-organized Architecture
Jia Liu,Maoguo Gong,Haibo He +2 more
TL;DR: This paper proposes an efficient architecture learning model for the nucleus based on the principle that more relevant input and output neuron pair deserves higher connecting density and finds that NNN achieves significant improvement over architectures with regular layers on the reconstructed dataset.
Evolutionary Multitasking Optimization for Multiobjective Hyperspectral Band Selection
TL;DR: In this article , the evolutionary multitasking optimization algorithm has the characteristics of processing multiple tasks at the same time to improve the search efficiency, and the evolutionary multi-task optimization algorithm is used as search strategy to select the band subset.
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Hierarchical Multimodal Transformer to Summarize Videos
TL;DR: Wang et al. as mentioned in this paper proposed a hierarchical transformer for video summarization, which can capture the dependencies among frame and shots, and summarize the video by exploiting the scene information formed by shots.
Multi-regularization sparse reconstruction based on multifactorial multiobjective optimization
Wenmin Han,Hao Li,Maoguo Gong +2 more
TL;DR: In this paper , a multi-regularization based on multifactorial multiobjective optimization is proposed to solve the sparse reconstruction problem, where the sparsity and reconstruction error can be considered as two objectives.