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Books and Theses
- 2012
[b1]Nguyen Thai-Nghe:
Predicting Student Performance in an Intelligent Tutoring System. University of Hildesheim, 2012
Journal Articles
- 2024
- [j6]Luyl-Da Quach
, Khang Quoc Nguyen, Anh Quynh Nguyen, Hoang Ngoc Tran, Nguyen Thai-Nghe:
Tomato Health Monitoring System: Tomato Classification, Detection, and Counting System Based on YOLOv8 Model With Explainable MobileNet Models Using Grad-CAM++. IEEE Access 12: 9719-9737 (2024) - [j5]Le Huynh Quoc Bao, Huynh Huu Bao Khoa, Nguyen Thai-Nghe:
An Ensemble Model for Combining Deep Matrix Factorization and Image-Based Recommendation Systems. SN Comput. Sci. 5(6): 674 (2024) - 2023
- [j4]Luyl-Da Quach, Khang Quoc Nguyen, Anh Quynh Nguyen, Nguyen Thai-Nghe, Tri Gia Nguyen:
Explainable Deep Learning Models With Gradient-Weighted Class Activation Mapping for Smart Agriculture. IEEE Access 11: 83752-83762 (2023) - [j3]Huynh-Ly Thanh-Nhan, Le Huy-Thap, Nguyen Thai-Nghe:
Deep Biased Matrix Factorization for Student Performance Prediction. EAI Endorsed Trans. Context aware Syst. Appl. 9(1): e4 (2023) - 2022
- [j2]Tran Thanh Dien, Nguyen Thanh Hai, Nguyen Thai-Nghe:
An approach for learning resource recommendation using deep matrix factorization. J. Inf. Telecommun. 6(4): 381-398 (2022) - 2020
- [j1]Thanh Hai Nguyen, Nguyen Thai-Nghe:
Diagnosis Approaches for Colorectal Cancer Using Manifold Learning and Deep Learning. SN Comput. Sci. 1(5): 281 (2020)
Conference and Workshop Papers
- 2024
- [c47]Nguyen Thai-Nghe, Vo Van Kiet, Huu-Hoa Nguyen:
Brain Tumor Segmentation with FPN-Based EfficientNet and XAI. ACIIDS (2) 2024: 109-119 - 2023
- [c46]Nguyen Xuan Ha Giang, Lam Thanh Toan, Nguyen Thai-Nghe:
Session-Based Recommendation System Approach for Predicting Learning Performance. FDSE 2023: 312-327 - [c45]Nguyen Thai-Nghe, Tran Khanh Dong, Hoang Xuan Tri, Nguyen Chi-Ngon:
Deep Learning Approach for Tomato Leaf Disease Detection. FDSE 2023: 572-579 - [c44]Nguyen Thai-Nghe, Nguyen Thi Kim Xuyen, An Cong Tran, Tran Thanh Dien:
Dealing with New User Problem Using Content-Based Deep Matrix Factorization. IEA/AIE (2) 2023: 177-188 - [c43]An Cong Tran, Duc-Thien Tran, Nguyen Thai-Nghe, Tran Thanh Dien, Hai Thanh Nguyen:
Course Recommendation Based on Graph Convolutional Neural Network. IEA/AIE (1) 2023: 235-240 - 2022
- [c42]Marcin Jodlowiec, Adriana Albu, Krzysztof Wolk, Nguyen Thai-Nghe, Adrian Karasinski:
Layer-Wise Optimization of Contextual Neural Networks with Dynamic Field of Aggregation. ACIIDS (2) 2022: 302-312 - [c41]Nguyen Thai-Nghe, Hai Thanh Nguyen, Tran Thanh Dien:
Recommendations in E-Commerce Systems Based on Deep Matrix Factorization. FDSE (CCIS Volume) 2022: 419-431 - [c40]Hai Thanh Nguyen, Anh Duy Le, Nguyen Thai-Nghe, Tran Thanh Dien:
An Approach for Similarity Vietnamese Documents Detection from English Documents. FDSE (CCIS Volume) 2022: 574-587 - [c39]Nguyen Thai-Nghe, Pham Hong Sang:
A Session-Based Recommender System for Learning Resources. FDSE (CCIS Volume) 2022: 706-713 - [c38]Nguyen Van-Binh, Nguyen Thai-Nghe:
Cardiovascular Disease Detection on X-Ray Images with Transfer Learning. IEA/AIE 2022: 173-183 - [c37]Huynh Thanh-Du, Maciej Huk, Nguyen Hung Dung, Nguyen Thai-Nghe:
An Attendance Checking System on Mobile Devices Using Transfer Learning. SoMeT 2022: 499-506 - 2021
- [c36]Tran Thanh Dien, Le Duy-Anh, Nguyen Hong-Phat, Nguyen Van-Tuan, Trinh Thanh-Chanh, Le Minh-Bang, Hai Thanh Nguyen, Nguyen Thai-Nghe:
Four Grade Levels-Based Models with Random Forest for Student Performance Prediction at a Multidisciplinary University. CISIS 2021: 1-12 - [c35]Huong Thu Thi Luong, Huong Hoang Luong, Hai Thanh Nguyen, Nguyen Thai-Nghe:
Hospital Revenue Forecast Using Multivariate and Univariate Long Short-Term Memories. FDSE (CCIS Volume) 2021: 50-65 - [c34]Tran Thanh Dien, Pham Huu Phuoc, Nguyen Thanh Hai, Nguyen Thai-Nghe:
Personalized Student Performance Prediction Using Multivariate Long Short-Term Memory. FDSE (CCIS Volume) 2021: 238-247 - [c33]Huynh-Ly Thanh-Nhan, Le Huy-Thap, Nguyen Thai-Nghe:
Integrating Deep Learning Architecture into Matrix Factorization for Student Performance Prediction. FDSE 2021: 408-423 - [c32]Tran Thanh Dien, Hai Thanh Nguyen, Nguyen Thai-Nghe:
Deep Matrix Factorization for Learning Resources Recommendation. ICCCI 2021: 167-179 - 2020
- [c31]Nguyen Thai-Nghe, Tran Thanh Hung, Nguyen Chi-Ngon:
A Forecasting Model for Monitoring Water Quality in Aquaculture and Fisheries IoT Systems. ACOMP 2020: 165-169 - [c30]Tran Thanh Dien, Luu Hoai-Sang, Nguyen Thanh Hai, Nguyen Thai-Nghe:
Course Recommendation with Deep Learning Approach. FDSE (CCIS Volume) 2020: 63-77 - [c29]Nguyen Thai-Nghe, Nguyen Thanh Hai:
Forecasting Sensor Data Using Multivariate Time Series Deep Learning. FDSE (CCIS Volume) 2020: 215-229 - [c28]Nguyen Thanh Hai, Toan Bao Tran, An Cong Tran, Nguyen Thai-Nghe:
Feature Selection Using Local Interpretable Model-Agnostic Explanations on Metagenomic Data. FDSE (CCIS Volume) 2020: 340-357 - [c27]Linh My Thi Ong, Nguyen Thai-Nghe, Huong Hoang Luong, Nghi C. Tran, Hiep Xuan Huynh:
Cyber Physical System: Achievements and challenges. ICMLSC 2020: 129-133 - [c26]Tran Thanh Dien, Le Van Trung, Nguyen Thai-Nghe:
An approach for semantic-based searching in learning resources. KSE 2020: 183-188 - 2019
- [c25]Tran Thanh Dien, Bui Huu Loc, Nguyen Thai-Nghe:
Article Classification using Natural Language Processing and Machine Learning. ACOMP 2019: 78-84 - [c24]Nguyen Hong Son, Nguyen Thai-Nghe:
Deep Learning for Rice Quality Classification. ACOMP 2019: 92-96 - [c23]Thanh Hai Nguyen, Nguyen Thai-Nghe:
Disease Prediction Using Metagenomic Data Visualizations Based on Manifold Learning and Convolutional Neural Network. FDSE 2019: 117-131 - [c22]Tran Thanh Dien, Huynh Ngoc Han, Nguyen Thai-Nghe:
An Approach for Plagiarism Detection in Learning Resources. FDSE 2019: 722-730 - 2017
- [c21]Nguyen Thai-Nghe, Mai Nhut-Tu, Huu-Hoa Nguyen:
An Approach for Multi-Relational Data Context in Recommender Systems. ACIIDS (1) 2017: 709-720 - [c20]Huynh Thanh-Tai, Nguyen Thai-Nghe:
A Semantic-Based Recommendation Approach for Cold-Start Problem. FDSE 2017: 433-443 - [c19]Huynh-Ly Thanh-Nhan, Le Huy-Thap, Nguyen Thai-Nghe:
Toward integrating social networks into intelligent tutoring systems. KSE 2017: 112-117 - 2016
- [c18]Nguyen Thanh Hai, Huu-Hoa Nguyen, Nguyen Thai-Nghe:
A Mobility Prediction Model for Location-Based Social Networks. ACIIDS (1) 2016: 106-115 - [c17]Luu Nguyen Anh-Thu, Huu-Hoa Nguyen, Nguyen Thai-Nghe:
A Context-Aware Implicit Feedback Approach for Online Shopping Recommender Systems. ACIIDS (2) 2016: 584-593 - [c16]Huynh Thanh-Tai, Huu-Hoa Nguyen, Nguyen Thai-Nghe:
A Semantic Approach in Recommender Systems. FDSE 2016: 331-343 - [c15]Huynh-Ly Thanh-Nhan, Huu-Hoa Nguyen, Nguyen Thai-Nghe:
Methods for building course recommendation systems. KSE 2016: 163-168 - 2015
- [c14]Nguyen Thai-Nghe, Quoc Dinh Truong:
An Approach for Building a Semi-automatic Online Consultancy System. ACOMP 2015: 51-58 - [c13]Tran Nguyen Minh-Thai, Nguyen Thai-Nghe:
An Approach for Developing Intelligent Systems in Smart Home Environment. FDSE 2015: 147-161 - [c12]Nguyen Thai-Nghe, Lars Schmidt-Thieme:
Multi-relational Factorization Models for Student Modeling in Intelligent Tutoring Systems. KSE 2015: 61-66 - [c11]Tran Nguyen Minh-Thai, Nguyen Thai-Nghe:
Methods for Abnormal Usage Detection in Developing Intelligent Systems for Smart Homes. KSE 2015: 114-119 - 2014
- [c10]Nguyen Thai-Nghe, Nguyen Chi-Ngon:
An approach for building an intelligent parking support system. SoICT 2014: 192-201 - 2012
- [c9]Lucas Drumond, Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme:
Factorization techniques for student performance classification and ranking. UMAP Workshops 2012 - [c8]Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Lars Schmidt-Thieme:
Using factorization machines for student modeling. UMAP Workshops 2012 - 2011
- [c7]Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Alexandros Nanopoulos, Lars Schmidt-Thieme:
Matrix and Tensor Factorization for Predicting Student Performance. CSEDU (1) 2011: 69-78 - [c6]Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme:
Factorization Models for Forecasting Student Performance. EDM 2011: 11-20 - [c5]Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme:
Personalized Forecasting Student Performance. ICALT 2011: 412-414 - [c4]Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme:
A new evaluation measure for learning from imbalanced data. IJCNN 2011: 537-542 - 2010
- [c3]Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme:
Cost-sensitive learning methods for imbalanced data. IJCNN 2010: 1-8 - [c2]Nguyen Thai-Nghe, Lucas Drumond, Artus Krohn-Grimberghe, Lars Schmidt-Thieme:
Recommender system for predicting student performance. RecSysTEL@RecSys 2010: 2811-2819 - 2009
- [c1]Nguyen Thai-Nghe, André Busche, Lars Schmidt-Thieme:
Improving Academic Performance Prediction by Dealing with Class Imbalance. ISDA 2009: 878-883
Parts in Books or Collections
- 2013
- [p1]Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme:
An Evaluation Measure for Learning from Imbalanced Data Based on Asymmetric Beta Distribution. Classification and Data Mining 2013: 121-129
Coauthor Index
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