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Journals peer-reviewed by Scopus
Nguyen, V.H. and Tran, N.N. (2024) Combining dynamic and static host intrusion detection features using variational long short-term memory recurrent autoencoder Объединение преимуществ динамического и статического обнаружения вторжений с использованием вариационного рекуррентного автокодировщика с долгой краткосрочной памятью. Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy Upravleniya, 20 (1). pp. 34-51. ISSN 18119905
Nguyen, H.N. and Tran, N.N. and Cao, V.L. (2023) Deep Clustering Based Latent Representation for IoT Malware Detection. In: UNSPECIFIED.
Nguyen, H.N. and Tran, N.N. and Hoang, T.H. and Cao, V.L. (2022) Denoising Latent Representation with SOMs for Unsupervised IoT Malware Detection. SN Computer Science, 3 (6). ISSN 2662995X
Van, T.P. and Nguyen, S.T. and Doan, L.B. and Tran, N.N. and Thanh, T.M. (2020) Efficient Palm-Line Segmentation with U-Net Context Fusion Module. In: 14th International Conference on Advanced Computing and Applications, ACOMP 2020, 25 November 2020 through 27 November 2020.
Pham, Q.H. and Anh Nguyen, V. and Doan, L.B. and Tran, N.N. and Thanh, T.M. (2020) From Universal Language Model to Downstream Task: Improving RoBERTa-Based Vietnamese Hate Speech Detection. In: 12th International Conference on Knowledge and Systems Engineering, KSE 2020, 12 November 2020 through 14 November 2020.
Van, T.P. and Nguyen, T.M. and Tran, N.N. and Nguyen, H.V. and Doan, L.B. and Dao, H.Q. and Minh, T.T. (2020) Interpreting the Latent Space of Generative Adversarial Networks using Supervised Learning. In: 14th International Conference on Advanced Computing and Applications, ACOMP 2020, 25 November 2020 through 27 November 2020.
Huu, Q.P. and Dinh, T.H. and Tran, N.N. and Van, T.P. and Minh, T.T. (2019) Deep neural networks based invisible steganography for audio-into-image algorithm. In: 8th IEEE Global Conference on Consumer Electronics, GCCE 2019, 15 October 2019 through 18 October 2019.
Others
Tran, N.N. (2020) Giới thiệu về TensorRT. [Teaching Resource]