7 Papers
2 Citations
Ly Van Tran is an academic researcher from Vietnam National University, Ho Chi Minh City. The author has contributed to research in topics: Computer science & Feature selection. The author has an hindex of 2, co-authored 4 publications.
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Papers
Early Disease Classification of Mango Leaves Using Feed-Forward Neural Network and Hybrid Metaheuristic Feature Selection
TL;DR: This research aims at detecting early disease on plant leaves with small disease blobs, which can only be detected with higher resolution images, by an artificial neural network (ANN) approach and compares the results with another approach using popular CNN models enhanced with transfer learning.
Application of Machine Learning in Epileptic Seizure Detection
Ly Van Tran,H. M. Tran,Tuan Minh Le,Tri T. M. Huynh,H. T. Tran,Son V. T. Dao +5 more
TL;DR: In this article , a machine learning-based approach for detecting epileptic seizures in EEG signals is presented. But, the proposed method is not suitable for the detection of epileptic seizure in clinical applications.
A Feature Selection Approach for Fall Detection Using Various Machine Learning Classifiers
TL;DR: Wang et al. as mentioned in this paper proposed a novel feature subset selection to reduce the number of effective input attributes based on a hybridized metaheuristic - an adaptive particle swarm and Grey Wolf Optimization (APGWO).
Real-Time Size and Mass Estimation of Slender Axi-Symmetric Fruit/Vegetable Using a Single Top View Image.
TL;DR: A method to estimate the mass/volume of agricultural products with axi-symmetrical shapes such as a carrot or a cucumber is developed and proved to be sufficiently accurate, easy to use, and rotationally invariant.
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An Analysis of Vocal Features for Parkinson’s Disease Classification Using Evolutionary Algorithms
TL;DR: In this article , a machine learning-based approach for classifying healthy people from people with the disease utilizing Grey Wolf Optimization (GWO) for feature selection, along with Light Gradient Boosted Machine (LGBM) to optimize the model performance.