TRƯỜNG CÔNG NGHỆ THÔNG TIN & TRUYỀN THÔNG
Khu II đường 3/2, P. Ninh Kiều, TP. Cần Thơ, Việt Nam
TRƯỜNG CÔNG NGHỆ THÔNG TIN & TRUYỀN THÔNG
Khu II đường 3/2, P. Ninh Kiều, TP. Cần Thơ, Việt Nam
Tập trung vào những công nghệ định hình tương lai số
Machine Learning, Deep Learning, Generative AI, Computer Vision, Natural Language Processing.
Big Data, Data Analytics, Data Mining, Business Intelligence và các phương pháp khai thác dữ liệu.
Software Engineering, Web & Mobile Applications, Distributed Systems, Cloud Computing.
Network Security, Cybersecurity, Cryptography, IoT Security và bảo vệ dữ liệu.
Các nghiên cứu về trí tuệ nhân tạo đang mở ra những hướng tiếp cận mới trong giáo dục, nông nghiệp, y tế, quản lý và phát triển đô thị thông minh.
Cập nhật những hoạt động, thành tựu và dấu ấn nghiên cứu
Nghiên cứu tạo ra những thay đổi có ý nghĩa cho cộng đồng
Kết nối với các nhà nghiên cứu, khám phá cơ hội hợp tác và cùng phát triển những giải pháp công nghệ cho cộng đồng và xã hội.
| # | Type | Final Citation |
|---|---|---|
| 1 | WoS | nnnnnnnnnnnnnnnnnnnnnnnnnnnn |
| 2 | Thai-Nghe, N., Lan, L. V. H., & Hung, H. T. (2025). Resource-Constrained Optimization of E-Commerce Recommendation Systems. In Communications in Computer and Information Science (pp. 199–211). Springer Nature Singapore. https://doi.org/10.1007/978-981-95-4724-1_14 | |
| 7 | Tran, M.-T., Nguyen, T.-N., & Do, T.-N. (2025). Bagged CoAtNet for Improving Intangible Cultural Heritage Image Classification. In Communications in Computer and Information Science (pp. 416–428). Springer Nature Singapore. https://doi.org/10.1007/978-981-95-4721-0_28 | |
| 8 | Quach, L.-D., Le, D.-T., Nguyen, C.-N., & Thai-Nghe, N. (2025). Explainable AI for Agriculture: Teacher-Student Learning in Rice Pest Classification. In Communications in Computer and Information Science (pp. 31–45). Springer Nature Singapore. https://doi.org/10.1007/978-981-95-3355-8_3 | |
| 9 | Tuyet, H. N., Phuc, N. T., & Thai-Nghe, N. (2025). Tomato Leaf Classification Using GAN-Generated Images. In Communications in Computer and Information Science (pp. 19–30). Springer Nature Singapore. https://doi.org/10.1007/978-981-95-3358-9_2 | |
| 10 | Tran, D.-Q., Khiem, N. M., & Thai-Nghe, N. (2025). An Explainable Biased Multi-relational Matrix Factorization Model Using XAI for Recommendation Systems. In Communications in Computer and Information Science (pp. 105–116). Springer Nature Singapore. https://doi.org/10.1007/978-981-95-3355-8_8 | |
| 11 | Cam-Nhung, M. T., & Thai-Nghe, N. (2025). Graph Neural Networks with Transformer for Sequential Recommendation. SN Computer Science, 6(7). https://doi.org/10.1007/s42979-025-04343-0 | |
| 12 | NGUYEN, H., VO, V., & NGUYEN, T. (2025). A Chatbot‐integrated Deep Learning Approach for Rice Leaf Disease Detection in the Mekong Delta Region of Vietnam. In Chatbots and Beyond (pp. 211–239). Wiley. https://doi.org/10.1002/9781394411283.ch11 | |
| 13 | Tran, M.-T., Pham, T.-P., Nguyen, T.-N., & Do, T.-N. (2025). Classifying Intangible Cultural Heritage Images in the Mekong Delta. SN Computer Science, 6(6). https://doi.org/10.1007/s42979-025-04117-8 | |
| 14 | Thai-Nghe, N., Van, P. T. B., Cam-Nhung, M. T., & Hung, N. B. (2025). Improving University Quality from Student Feedback with Sentiment Analysis. In Lecture Notes in Computer Science (pp. 343–354). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-8892-0_29 | |
| 15 | Xuan-Ha-Giang Nguyen, Thanh-Toan Luong, Thai-Nghe Nguyen (2025). An Approach for Dealing with Sequential Data in Intelligent Tutoring Systems. Journal on Information Technologies & Communications. No 2, Vol 2025, Vietnam Ministry of Information and Communications (MIC) | |
| 16 | Thai-Nghe, N., Thao, N. T., Bao, L. H. Q., & Tuan, T. M. (2025). Detecting Scratches in Microbiological Piping Using USB Camera and Deep Learning. In Communications in Computer and Information Science (pp. 145–156). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-98164-7_12 | |
| 17 | Khiem, N. M., Van Thanh, T., Hai, N. T., Bao, L. H. Q., & Nghe, N. T. (2025). An Approach for Enhancing Ripe Tomato Classification and Counting by Using Deep Learning and SAHI Image Processing. In Communications in Computer and Information Science (pp. 86–99). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-98167-8_7 | |
| 18 | Luong, H. H., Nguyen, H. T., & Thai-Nghe, N. (2025). EfficientPhoCaption: An Enhanced PhoBERT-Based Image Captioning Framework for Breast Cancer Diagnosis. SN Computer Science, 6(6). https://doi.org/10.1007/s42979-025-04188-7 | |
| 19 | Quach, L.-D., Thai-Nghe, N., & Nguyen, C.-N. (2025). Explainable Dual-Branch Hybrid Model for Maize Leaf Disease Classification. SN Computer Science, 6(6). https://doi.org/10.1007/s42979-025-04102-1 | |
| 20 | Quach, L.-D., Quoc Khang, N., Thai-Nghe, N., & Nguyen, C.-N. (2025). XAI-BO: an architecture using Grad-CAM technique to evaluate Bayesian optimization algorithms on deep learning models. Journal of Information and Telecommunication, 9(3), 335–356. https://doi.org/10.1080/24751839.2024.2447191 | |
| 21 | Trần, T. Đ., Trần, T. T. L., Lê, D. A., Nguyễn, T. K. Q., Nguyễn, B. Đ., Nguyễn, T. H., & Nguyễn, T. N. (2025). Phát hiện tương đồng hình ảnh trong bài báo khoa học bằng phương pháp xử lý ảnh kết hợp mạng học sâu ResNet50. CTU Journal of Science, 61(2), 44–53. https://doi.org/10.22144/ctujos.2025.046 | |
| 22 | Nguyen, H. T., Duong, K. H., Pham, L. T. T., Bui, P. H. D., Thai-Nghe, N., & Dien, T. T. (2025). Inverted Index for Similar Document Detection: A Case Study at Can Tho University Journal of Science. SN Computer Science, 6(3). https://doi.org/10.1007/s42979-025-03707-w | |
| 23 | Pham, N. H., Hoa, N. H., & Thai-Nghe, N. (2025). Enhanced Bone Fracture Diagnosis Using Threshold-Based Bone Extraction. In Lecture Notes in Networks and Systems (pp. 796–803). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-80943-9_84 | |
| 24 | Luong, H. H., Hong, P. P., Minh, D. V., Quang, T. N. L., The, A. D., Thai-Nghe, N., & Nguyen, H. T. (2025). Principal component analysis and fine-tuned vision transformation integrating model explainability for breast cancer prediction. Visual Computing for Industry, Biomedicine, and Art, 8(1). https://doi.org/10.1186/s42492-025-00186-x | |
| 25 | Luong, H. H., Thai-Nghe, N., & Nguyen, H. T. (2025). BCCNetAttention: Enhancing Breast Cancer Report Through Image Captioning with Convolution Neural Network and Transformers Architecture. In Lecture Notes in Computer Science (pp. 188–199). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-6389-7_16 | |
| 26 | Thi Cam-Nhung, M., Thuy Anh, N., & Thai-Nghe, N. (2024). Sequential Recommendation Using Graph Neuron Networks. In Communications in Computer and Information Science (pp. 66–79). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-0434-0_5 | |
| 27 | Thai-Nghe, N., Pham Minh, P., & Cam-Nhung, M. T. (2024). An Approach for Movie Recommendation Using Deep Matrix Factorization. In Communications in Computer and Information Science (pp. 237–248). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-0437-1_18 | |
| 28 | Luong, H. H., Nguyen, H. T., & Thai-Nghe, N. (2024). Toward Supporting Breast Cancer Diagnosis Based on Captioning Mammogram and Ultrasound Images. In Communications in Computer and Information Science (pp. 71–85). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-9616-8_6 | |
| 29 | Quach, L.-D., Quoc, K. N., Nguyen, C.-N., & Thai-Nghe, N. (2024). Explainable AI for Plant Disease Detection: Assessing Explainability in Classifying Maize Leaves Diseases with Focus Score and Ablation-CAM. In Communications in Computer and Information Science (pp. 19–32). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-9613-7_2 | |
| 30 | Luong, H. H., Pham, K. T., Le, D. T., Thanh, D. L. P., Hai, L. L. H., Nguyen, H. N., Thai-Nghe, N., & Nguyen, H. T. (2024). An Approach for Breast Cancer X-Ray Images Classification Based on Vision Transformer. Vietnam Journal of Computer Science, 12(03), 329–347. https://doi.org/10.1142/s2196888824500210 | |
| 31 | Tran, M.-T., Pham, T.-P., Thai-Nghe, N., & Do, T.-N. (2024). Fusing Models for Classifying Intangible Cultural Heritage Images in the Mekong Delta. In Communications in Computer and Information Science (pp. 202–212). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-9616-8_16 | |
| 32 | Hoang Luong, H., Thanh Nguyen, H., & Thai-Nghe, N. (2024). Detection and classification of breast cancer in mammographic images with fine-tuned convolutional neural networks. Journal of Information and Telecommunication, 9(2), 209–236. https://doi.org/10.1080/24751839.2024.2415033 | |
| 33 | Bao, L. H. Q., Khoa, H. H. B., & Thai-Nghe, N. (2024). An Ensemble Model for Combining Deep Matrix Factorization and Image-Based Recommendation Systems. SN Computer Science, 5(6). https://doi.org/10.1007/s42979-024-02978-z | |
| 34 | Thai-Nghe, N., Van Kiet, V., & Huu-Hoa, N. (2024). Brain Tumor Segmentation with FPN-Based EfficientNet and XAI. In Lecture Notes in Computer Science (pp. 109–119). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-4985-0_9 | |
| 35 | Luong, H. H., Vo, M. D., Phan, H. P., Dinh, T. A., Nguyen, L. Q. T., Tran, Q. T., Thai-Nghe, N., & Nguyen, H. T. (2024). Improving breast cancer prediction via progressive ensemble and image enhancement. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-024-19299-1 | |
| 36 | Luong, H. H., Nguyen, H. T., & Thai-Nghe, N. (2024). AEGANB3: An Efficient Framework with Self-attention Mechanism and Deep Convolutional Generative Adversarial Network for Breast Cancer Classification. International Journal of Advanced Computer Science and Applications, 15(5). https://doi.org/10.14569/ijacsa.2024.01505139 | |
| 37 | Thai-Nghe, N., Thanh-Son, P., & Huu-Hoa, N. (2024). Human Detection in Video for Security Surveillance Systems. In Studies in Systems, Decision and Control (pp. 123–133). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-63929-6_12 | |
| 38 | Thai-Nghe, N., Vi, N. Q., & Chi-Ngon, N. (2024). Fruit Calorie Determination System for Dieters and Athletes Using Deep Learning. In Studies in Systems, Decision and Control (pp. 213–220). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-63929-6_19 | |
| 39 | Nguyen, H. T., Nguyen, D. T., Tran, T. T., Nguyen, H.-H., & Thai-Nghe, N. (2024). Fake Face Detection with Separable Convolutions. In Studies in Systems, Decision and Control (pp. 135–147). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-63929-6_13 | |
| 40 | Quach, L.-D., Quoc, K. N., Quynh, A. N., Ngoc, H. T., & Thai-Nghe, N. (2024). 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. https://doi.org/10.1109/access.2024.3351805 | |
| 41 | Dien, T. T., Thanh-Hai, N., & Thai-Nghe, N. (2023). Novel Approaches for Searching and Recommending Learning Resources. Cybernetics and Information Technologies, 23(2), 151–169. https://doi.org/10.2478/cait-2023-0019 | |
| 42 | Luong, H. H., Nguyen, H. T., & Thai-Nghe, N. (2023). A Combination of Active Learning and Deep Learning for Improving Breast Cancer Prediction. In Lecture Notes in Networks and Systems (pp. 3–10). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-49529-8_1 | |
| 43 | Thai-Nghe, N., Dong, T. K., Tri, H. X., & Chi-Ngon, N. (2023). Deep Learning Approach for Tomato Leaf Disease Detection. In Communications in Computer and Information Science (pp. 572–579). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-8296-7_42 | |
| 44 | Thai-Nghe, N., Hong, N. M., Nhu, P. T. B., & Hai, N. T. (2023). Classification of Pneumonia on Chest X-ray Images Using Transfer Learning. In Lecture Notes on Data Engineering and Communications Technologies (pp. 85–93). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-46749-3_9 | |
| 45 | Thai-Nghe, N., Nguyen, H.-H., Park, W., Ngo, Q. T., & Truong, M. T. (2023). Human Intrusion Detection for Security Cameras Using YOLOv8. In Communications in Computer and Information Science (pp. 220–227). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-7666-9_19 | |
| 46 | Giang, N. X. H., Thanh-Toan, L., & Thai-Nghe, N. (2023). Session-Based Recommendation System Approach for Predicting Learning Performance. In Communications in Computer and Information Science (pp. 312–327). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-8296-7_22 | |
| 47 | Bao, L. H. Q., Khoa, H. H. B., & Thai-Nghe, N. (2023). Image Recommendation Based on Pre-trained Deep Learning and Similarity Matching. In Communications in Computer and Information Science (pp. 258–270). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-7649-2_20 | |
| 48 | Thai-Nghe, N., Minh-Tan, T., Hai, L. M., & Thanh-Hai, N. (2023). FaceMask Detection Using Transfer Learning. In Communications in Computer and Information Science (pp. 212–219). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-7666-9_18 | |
| 49 | Quach, L.-D., Quoc, K. N., Quynh, A. N., Thai-Nghe, N., & Nguyen, T. G. (2023). Explainable Deep Learning Models With Gradient-Weighted Class Activation Mapping for Smart Agriculture. IEEE Access, 11, 83752–83762. https://doi.org/10.1109/access.2023.3296792 | |
| 50 | Thai-Nghe, N., Xuyen, N. T. K., Tran, A. C., & Dien, T. T. (2023). Dealing with New User Problem Using Content-Based Deep Matrix Factorization. In Lecture Notes in Computer Science (pp. 177–188). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-36822-6_16 | |
| 51 | Tran, A. C., Tran, D.-T., Thai-Nghe, N., Dien, T. T., & Nguyen, H. T. (2023). Course Recommendation Based on Graph Convolutional Neural Network. In Lecture Notes in Computer Science (pp. 235–240). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-36819-6_20 | |
| 52 | Thai-Nghe N, Hua M-N, Nguyen B-A. CLASSIFICATION OF ARTICLES USING MACHINE LEARNING: CASE STUDY OF TRA VINH UNIVERSITY JOURNAL OF SCIENCE, VIETNAM. journal [Internet]. 20Jul.2023 [cited 26Apr.2024];13(6). Available from: https://journal.tvu.edu.vn/index.php/journal/article/view/2108 | |
| 53 | Huynh-Ly, T.-N., Le, H.-T., & Thai-Nghe, N. (2023). Deep Biased Matrix Factorization for Student Performance Prediction. EAI Endorsed Transactions on Context-Aware Systems and Applications, 9(1), e4. https://doi.org/10.4108/eetcasa.v9i1.3147 | |
| 54 | Van-Quoc, V., & Thai-Nghe, N. (2023). Skin Diseases Detection with Transfer Learning. In Lecture Notes in Networks and Systems (pp. 139–150). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-6631-6_11 | |
| 55 | Quach, L.-D., Quynh, A. N., Quoc, K. N., & Thai, N. N. (2023). Using Optimization Algorithm to Improve the Accuracy of the CNN Model on the Rice Leaf Disease Dataset. In Smart Innovation, Systems and Technologies (pp. 535–544). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-7447-2_47 | |
| 56 | Thai-Nghe, N., Thanh-Hai, N., & Dien, T. T. (2022). Recommendations in E-Commerce Systems Based on Deep Matrix Factorization. In Communications in Computer and Information Science (pp. 419–431). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-8069-5_28 | |
| 57 | Jodłowiec, M., Albu, A., Wołk, K., Thai-Nghe, N., & Karasiński, A. (2022). Layer-Wise Optimization of Contextual Neural Networks with Dynamic Field of Aggregation. In Lecture Notes in Computer Science (pp. 302–312). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-21967-2_25 | |
| 58 | Nguyen, H. T., Le, A. D., Thai-Nghe, N., & Dien, T. T. (2022). An Approach for Similarity Vietnamese Documents Detection from English Documents. In Communications in Computer and Information Science (pp. 574–587). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-8069-5_39 | |
| 59 | Thanh Nguyen, H., Kieu Nguyen, T., Tri Pham, M., Le Hoang Tran, C., Thanh Dien, T., & Thai-Nghe, N. (2022). Similar Vietnamese Document Detection in Online Assignment Submission System. In Studies in Computational Intelligence (pp. 251–264). Springer International Publishing. https://doi.org/10.1007/978-3-031-08580-2_23 | |
| 60 | Thai-Nghe, N., & Sang, P. H. (2022). A Session-Based Recommender System for Learning Resources. In Communications in Computer and Information Science (pp. 706–713). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-8069-5_51 | |
| 61 | Dien, T. T., Thanh-Hai, N., & Thai-Nghe, N. (2022). An approach for learning resource recommendation using deep matrix factorization. Journal of Information and Telecommunication, 6(4), 381–398. https://doi.org/10.1080/24751839.2022.2058250 | |
| 62 | Thanh-Du, H., Huk, M., Hung Dung, N., & Thai-Nghe, N. (2022). An Attendance Checking System on Mobile Devices Using Transfer Learning. In Frontiers in Artificial Intelligence and Applications. IOS Press. https://doi.org/10.3233/faia220279 | |
| 63 | Van-Binh, N., & Thai-Nghe, N. (2022). Cardiovascular Disease Detection on X-Ray Images with Transfer Learning. In Lecture Notes in Computer Science (pp. 173–183). Springer International Publishing. https://doi.org/10.1007/978-3-031-08530-7_15 | |
| 64 | Thai-Nghe, N., Tri, N. T., & Hoa, N. H. (2022). Deep Learning for Rice Leaf Disease Detection in Smart Agriculture. In Lecture Notes on Data Engineering and Communications Technologies (pp. 659–670). Springer International Publishing. https://doi.org/10.1007/978-3-030-97610-1_52 | |
| # | Type | Final Citation |
Dữ liệu hiển thị được cập nhật lúc 13:59 04/11/2026.

