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Thanh-Nghi Do
2020 – today
- 2024
- [j20]Thanh-Nghi Do, Minh-Thu Tran-Nguyen:
ImageNet classification with Raspberry Pis: federated learning algorithms of local classifiers. Int. J. Web Inf. Syst. 20(1): 48-65 (2024) - [j19]Thanh-Nghi Do
:
Enhancing Gene Expression Classification Through Explainable Machine Learning Models. SN Comput. Sci. 5(5): 606 (2024) - [j18]Omar Ettarguy
, Carole Delenne, Salem Benferhat, Ahlame Begdouri, Thanh-Nghi Do, Truong-Thanh Ma:
From GIS to Graphical Representation for Maintaining Connectivity of Wastewater Network Elements. SN Comput. Sci. 5(7): 851 (2024) - 2023
- [c57]Tri-Thuc Vo, Thanh-Nghi Do:
Biggest Margin Tree for the Multi-class Classification. FDSE 2023: 34-48 - [c56]Ti-Hon Nguyen, Thanh Ma, Thanh-Nghi Do:
LAVETTES: Large-scAle-dataset Vietnamese ExTractive TExt Summarization Models. FDSE 2023: 273-288 - [c55]Thanh-Tri Trang, Thanh Ma, Thanh-Nghi Do:
LORAP: Local Deep Neural Network for Solar Radiation Prediction. FDSE 2023: 366-380 - [c54]Thanh Ma, Thanh-Nghi Do, Nguyen-Khang Pham, Minh-Thu Tran-Nguyen, Tri-Thuc Vo, Salem Benferhat:
ViWaT: A Lightweight Ontology of the Vietnamese Wastewater Treatment Management with Biological Methodologies. ENIGMA@KR 2023: 24-34 - [c53]Tan-Hiep To, Thanh-Nghi Do, Duc-Nghia Ngo, Minh-Triet Tran, Trung-Nghia Le:
Budget-Aware Road Semantic Segmentation in Unseen Foggy Scenes. RIVF 2023: 171-176 - 2022
- [j17]Thanh-Nghi Do:
Incremental and parallel proximal SVM algorithm tailored on the Jetson Nano for the ImageNet challenge. Int. J. Web Inf. Syst. 18(2/3): 137-155 (2022) - [c52]Thanh-Nghi Do, Minh-Thu Tran-Nguyen:
ImageNet Challenging Classification with the Raspberry Pis: A Federated Learning Algorithm of Local Stochastic Gradient Descent Models. FDSE (CCIS Volume) 2022: 131-144 - [c51]Ti-Hon Nguyen, Thanh-Nghi Do:
Extractive Text Summarization on Large-scale Dataset Using K-Means Clustering. IEA/AIE 2022: 737-746 - [i1]Thanh-Nghi Do:
ImageNet Challenging Classification with the Raspberry Pi: An Incremental Local Stochastic Gradient Descent Algorithm. CoRR abs/2203.11853 (2022) - 2021
- [j16]Thanh-Nghi Do
:
Training Neural Networks on Top of Support Vector Machine Models for Classifying Fingerprint Images. SN Comput. Sci. 2(5): 355 (2021) - [c50]Thanh-Nghi Do:
Multi-class Bagged Proximal Support Vector Machines for the ImageNet Challenging Problem. FDSE 2021: 99-112 - [c49]Thanh-Nghi Do, Minh-Thu Tran-Nguyen, Thanh-Tri Trang, Tri-Thuc Vo:
Deep Networks for Monitoring Waterway Traffic in the Mekong Delta. MCO 2021: 315-326 - [c48]Thanh-Nghi Do, Minh-Thu Tran-Nguyen:
Training Deep Network Models for Fingerprint Image Classification. MCO 2021: 327-337 - 2020
- [j15]Minh-Thu Tran-Nguyen, Le-Diem Bui, Thanh-Nghi Do
:
Decision trees using local support vector regression models for large datasets. J. Inf. Telecommun. 4(1): 17-35 (2020) - [j14]Thanh-Nghi Do
:
Automatic Learning Algorithms for Local Support Vector Machines. SN Comput. Sci. 1(1): 2:1-2:11 (2020) - [j13]Phuoc-Hai Huynh
, Van Hoa Nguyen
, Thanh-Nghi Do:
Improvements in the Large p, Small n Classification Issue. SN Comput. Sci. 1(4): 207 (2020) - [c47]The-Phi Pham, Minh-Thu Tran-Nguyen, Minh-Tan Tran, Thanh-Nghi Do:
Combining Support Vector Machines for Classifying Fingerprint Images. FDSE 2020: 399-410 - [c46]Thanh-Nghi Do, The-Phi Pham, Minh-Thu Tran-Nguyen:
Fine-tuning Deep Network Models for Classifying Fingerprint Images. KSE 2020: 79-84
2010 – 2019
- 2019
- [j12]Thanh-Nghi Do
, François Poulet:
Latent-lSVM classification of very high-dimensional and large-scale multi-class datasets. Concurr. Comput. Pract. Exp. 31(2) (2019) - [j11]Phuoc-Hai Huynh
, Van Hoa Nguyen
, Thanh-Nghi Do
:
Novel hybrid DCNN-SVM model for classifying RNA-sequencing gene expression data. J. Inf. Telecommun. 3(4): 533-547 (2019) - [j10]Thanh-Nghi Do, Le-Diem Bui:
Parallel Learning Algorithms of Local Support Vector Regression for Dealing with Large Datasets. Trans. Large Scale Data Knowl. Centered Syst. 41: 59-77 (2019) - [c45]Phuoc-Hai Huynh
, Van Hoa Nguyen
, Thanh-Nghi Do:
A Combined Enhancing and Feature Extraction Algorithm to Improve Learning Accuracy for Gene Expression Classification. FDSE 2019: 255-273 - [c44]Thanh-Nghi Do, The-Phi Pham, Nguyen-Khang Pham, Huu-Hoa Nguyen
, Karim Tabia, Salem Benferhat:
Stacking of SVMs for Classifying Intangible Cultural Heritage Images. ICCSAMA 2019: 186-196 - [c43]Phuoc-Hung Vo
, Thai-Son Nguyen
, Van-Thanh Huynh
, Thanh-C. Vo, Thanh-Nghi Do:
Secure and Robust Watermarking Scheme in Frequency Domain Using Chaotic Logistic Map Encoding. ICCSAMA 2019: 346-357 - [c42]Truong-Thanh Ma, Salem Benferhat, Zied Bouraoui, Karim Tabia, Thanh-Nghi Do, Nguyen-Khang Pham:
An Automatic Extraction Tool for Ethnic Vietnamese Thai Dances Concepts. ICMLA 2019: 1527-1530 - 2018
- [j9]Phuoc-Hung Vo
, Thai-Son Nguyen
, Van-Thanh Huynh
, Thanh-Nghi Do:
A novel reversible data hiding scheme with two-dimensional histogram shifting mechanism. Multim. Tools Appl. 77(21): 28777-28797 (2018) - [c41]Phuoc-Hai Huynh
, Van Hoa Nguyen
, Thanh-Nghi Do:
A Coupling Support Vector Machines with the Feature Learning of Deep Convolutional Neural Networks for Classifying Microarray Gene Expression Data. ACIIDS (Extended Posters) 2018: 233-243 - [c40]Minh-Thu Tran-Nguyen, Le-Diem Bui, Yong-Gi Kim, Thanh-Nghi Do:
Decision Tree Using Local Support Vector Regression for Large Datasets. ACIIDS (1) 2018: 255-265 - [c39]Truong-Thanh Ma, Salem Benferhat, Zied Bouraoui, Thanh-Nghi Do, Huu-Hoa Nguyen
:
Developing Application Based Upon An Ontology-Based Modelling of Vietnamese Traditional Dances. DigitalHERITAGE/VSMM 2018: 1-7 - [c38]Thanh-Nghi Do, Minh-Thu Tran-Nguyen:
Automatic Hyper-parameters Tuning for Local Support Vector Machines. FDSE 2018: 185-199 - [c37]Truong-Thanh Ma, Salem Benferhat, Zied Bouraoui, Karim Tabia, Thanh-Nghi Do, Huu-Hoa Nguyen
:
An Ontology-based Modelling of Vietnamese Traditional Dances (S). SEKE 2018: 64-67 - [c36]Phuoc-Hai Huynh
, Van Hoa Nguyen
, Thanh-Nghi Do:
Random ensemble oblique decision stumps for classifying gene expression data. SoICT 2018: 137-144 - 2017
- [j8]Thanh-Nghi Do, François Poulet:
Parallel Learning of Local SVM Algorithms for Classifying Large Datasets. Trans. Large Scale Data Knowl. Centered Syst. 31: 67-93 (2017) - [c35]Le-Diem Bui, Minh-Thu Tran-Nguyen, Yong-Gi Kim, Thanh-Nghi Do:
Parallel Algorithm of Local Support Vector Regression for Large Datasets. FDSE 2017: 139-153 - 2016
- [c34]Thanh-Nghi Do, François Poulet:
Régression logistique pour la classification d'images à grande échelle. EGC 2016: 309-320 - [c33]Thanh-Nghi Do, Minh-Thu Tran-Nguyen:
Incremental Parallel Support Vector Machines for Classifying Large-Scale Multi-class Image Datasets. FDSE 2016: 20-39 - [c32]Thanh-Nghi Do, François Poulet:
Classifying Very High-Dimensional and Large-Scale Multi-class Image Datasets with Latent-lSVM. UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld 2016: 714-721 - 2015
- [j7]Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet:
Large scale classifiers for visual classification tasks. Multim. Tools Appl. 74(4): 1199-1224 (2015) - [j6]Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich:
Classifying many-class high-dimensional fingerprint datasets using random forest of oblique decision trees. Vietnam. J. Comput. Sci. 2(1): 3-12 (2015) - [c31]Thanh-Nghi Do, François Poulet:
Random Local SVMs for Classifying Large Datasets. FDSE 2015: 3-15 - [c30]Thanh-Nghi Do:
Using Local Rules in Random Forests of Decision Trees. FDSE 2015: 32-45 - [c29]Thanh-Nghi Do:
Non-linear Classification of Massive Datasets with a Parallel Algorithm of Local Support Vector Machines. ICCSAMA 2015: 231-241 - [c28]Thanh-Nghi Do, François Poulet:
Parallel Multiclass Logistic Regression for Classifying Large Scale Image Datasets. ICCSAMA 2015: 255-266 - 2014
- [j5]Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet:
Parallel incremental power mean SVM for the classification of large-scale image datasets. Int. J. Multim. Inf. Retr. 3(2): 89-96 (2014) - [j4]Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet:
Classification d'images à grande échelle avec des SVM. Traitement du Signal 31(1-2): 39-56 (2014) - [j3]Thanh-Nghi Do:
Parallel multiclass stochastic gradient descent algorithms for classifying million images with very-high-dimensional signatures into thousands classes. Vietnam. J. Comput. Sci. 1(2): 107-115 (2014) - 2013
- [c27]Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet:
Multi-way classification for large scale visual object dataset. CBMI 2013: 185-190 - [c26]Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet:
Parallel incremental SVM for classifying million images with very high-dimensional signatures into thousand classes. IJCNN 2013: 1-8 - [c25]Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet:
Large Scale Visual Classification with Many Classes. MLDM 2013: 629-643 - [p3]Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet:
Large Scale Image Classification with Many Classes, Multi-features and Very High-Dimensional Signatures. Advanced Computational Methods for Knowledge Engineering 2013: 105-116
2000 – 2009
- 2009
- [c24]Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich, Nguyen-Khang Pham:
Classifying Very-High-Dimensional Data with Random Forests of Oblique Decision Trees. EGC (best of volume) 2009: 39-55 - [c23]Thanh-Nghi Do, Stéphane Lallich, Nguyen-Khang Pham, Philippe Lenca:
Un nouvel algorithme de forêts aléatoires d'arbres obliques particulièrement adapté à la classification de données en grandes dimensions. EGC 2009: 79-90 - [c22]François Poulet, Thanh-Nghi Do, Van Hoa Nguyen:
SVM incrémental et parallèle sur GPU. EGC 2009: 103-114 - [p2]Thanh-Nghi Do, François Poulet:
Kernel-Based Algorithms and Visualization for Interval Data Mining. Mining Complex Data 2009: 75-91 - 2008
- [j2]Nguyen-Khang Pham, Thanh-Nghi Do, François Poulet, Annie Morin:
TreeView, exploration interactive des arbres de décision. Rev. d'Intelligence Artif. 22(3-4): 473-487 (2008) - [j1]Thanh-Nghi Do, Jean-Daniel Fekete
:
V4Miner, un environnement de programmation visuelle pour la fouille de données. Rev. d'Intelligence Artif. 22(3-4): 503-517 (2008) - [c21]Thanh-Nghi Do, Van Hoa Nguyen
, François Poulet:
Speed Up SVM Algorithm for Massive Classification Tasks. ADMA 2008: 147-157 - [c20]Niklas Elmqvist
, Thanh-Nghi Do, Howard Goodell, Nathalie Henry, Jean-Daniel Fekete
:
ZAME: Interactive Large-Scale Graph Visualization. PacificVis 2008: 215-222 - [c19]Nguyen-Khang Pham, Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich:
Using Local Node Information in Decision Trees: Coupling a Local Labeling Rule with an Off-centered Entropy. DMIN 2008: 117-123 - [c18]Thanh-Nghi Do, Jean-Daniel Fekete, François Poulet:
Algorithmes rapides de boosting de SVM. EGC 2008: 297-308 - [c17]Thanh-Nghi Do, Van Hoa Nguyen
, François Poulet:
A Fast Parallel SVM Algorithm for Massive Classification Tasks. MCO 2008: 419-428 - [c16]Philippe Lenca, Stéphane Lallich, Thanh-Nghi Do, Nguyen-Khang Pham:
A Comparison of Different Off-Centered Entropies to Deal with Class Imbalance for Decision Trees. PAKDD 2008: 634-643 - [c15]Thanh-Nghi Do, Van Hoa Nguyen
:
A novel speed-up SVM algorithm for massive classification tasks. RIVF 2008: 215-220 - [p1]François Poulet, Thanh-Nghi Do:
Interactive Decision Tree Construction for Interval and Taxonomical Data. Visual Data Mining 2008: 123-135 - 2007
- [c14]Thanh-Nghi Do, Nguyen-Khang Pham, François Poulet:
Visualisation exploratoire des résultats d'algorithmes d'arbre de décision. EGC 2007: 157-168 - [c13]Thanh-Nghi Do, François Poulet:
Classification de grands ensembles de données avec un nouvel algorithme de SVM. EGC 2007: 739-750 - [c12]Thanh-Nghi Do, Jean-Daniel Fekete:
Large Scale Classification with Support Vector Machine Algorithms. ICMLA 2007: 7-12 - 2006
- [c11]Thanh-Nghi Do, François Poulet:
SVM incrémental, parallèle et distribué pour le traitement de grandes quantités de données. EGC 2006: 47-52 - [c10]Thanh-Nghi Do, François Poulet:
Kernel-based Algorithms and Visualization for Interval Data Mining. ICDM Workshops 2006: 295-299 - [c9]Thanh-Nghi Do, François Poulet:
Classifying one billion data with a new distributed svm algorithm. RIVF 2006: 59-66 - 2005
- [c8]Thanh-Nghi Do, François Poulet:
SVM et visualisation pour la fouille de grands ensembles de données. EGC 2005: 545-556 - [c7]Thanh-Nghi Do, François Poulet:
Mining Very Large Datasets with SVM and Visualization. ICEIS (2) 2005: 127-141 - 2004
- [c6]Thanh-Nghi Do, François Poulet:
Enhancing SVM with Visualization.. Discovery Science 2004: 183-194 - [c5]Thanh-Nghi Do, François Poulet:
Fouille de grands ensembles de données avec un boosting de Proximal SVM. EGC 2004: 229-239 - [c4]Thanh-Nghi Do, François Poulet:
Towards High Dimensional Data Mining with Boosting of PSVM and Visualization Tools. ICEIS (2) 2004: 36-41 - [c3]Thanh-Nghi Do, François Poulet:
SVM incrémental pour l'analyse d'expressions de gènes. RIVF 2004: 215-220 - 2003
- [c2]Thanh-Nghi Do, François Poulet:
Mining Very Large Datasets with Support Vector Machine Algorithms. ICEIS (2) 2003: 140-147 - [c1]Thanh-Nghi Do, François Poulet:
Fouille de textes avec proximal support vector machines. RIVF 2003: 33-36
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last updated on 2025-01-20 22:53 CET by the dblp team
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