Search Results for author: Loc Hoang Tran

Found 6 papers, 0 papers with code

Improved sparse PCA method for face and image recognition

no code implementations1 Dec 2021 Loc Hoang Tran, Tuan Tran, An Mai

Experimental results illustrate that the accuracy of the combination of the sparse PCA method (using the proximal gradient method and the FISTA method) and one specific classification system may be lower than the accuracy of the combination of the PCA method and one specific classification system but sometimes the combination of the sparse PCA method (using the proximal gradient method or the FISTA method) and one specific classification system leads to better accuracy.

Classification Face Recognition

Text classification problems via BERT embedding method and graph convolutional neural network

no code implementations30 Nov 2021 Loc Hoang Tran, Tuan Tran, An Mai

This paper presents the novel way combining the BERT embedding method and the graph convolutional neural network.

text-classification Text Classification

Directed hypergraph neural network

no code implementations9 Aug 2020 Loc Hoang Tran, Linh Hoang Tran

Among the classic directed graph based semi-supervised learning method, the novel directed hypergraph based semi-supervised learning method, the novel directed hypergraph neural network method that are utilized to solve this node classification task, we recognize that the novel directed hypergraph neural network achieves the highest accuracies.

General Classification Node Classification

Tensor Sparse PCA and Face Recognition: A Novel Approach

no code implementations12 Apr 2019 Loc Hoang Tran, Linh Hoang Tran

Face recognition is the important field in machine learning and pattern recognition research area.

Classification Face Recognition +1

Un-normalized hypergraph p-Laplacian based semi-supervised learning methods

no code implementations6 Nov 2018 Loc Hoang Tran, Linh Hoang Tran

Most network-based machine learning methods assume that the labels of two adjacent samples in the network are likely to be the same.

Hypergraph based semi-supervised learning algorithms applied to speech recognition problem: a novel approach

no code implementations28 Oct 2018 Loc Hoang Tran, Trang Hoang, Bui Hoang Nam Huynh

Most network-based speech recognition methods are based on the assumption that the labels of two adjacent speech samples in the network are likely to be the same.

speech-recognition Speech Recognition

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