Classification of acoustical signals by combining active learning strategies with semi-supervised learning schemes. Aridas C, Kanas VG, Karlos S, Kotsiantis S. S Karlos, C Aridas, VG Kanas, S Kotsiantis - Neural Computing and …, 2021 - Springer GSID: V4EGxx1e-WkJ
Semi-supervised active learning for sound classification in hybrid learning environments. Coutinho E, Schuller B. W Han, E Coutinho, H Ruan, H Li, B Schuller, X Yu… - PloS one, 2016 - journals.plos.org GSID: sLwlDpStjuAJ
Special issue on information, intelligence, systems and applications. Hatzilygeroudis I, Tsihrintzis G, Virvou M. I Hatzilygeroudis, G Tsihrintzis, M Virvou… - Neural Computing and …, 2023 - Springer GSID: vakHvvt8X4EJ
Revisiting Deep Active Learning for Semantic Segmentation. Brox T, Mittal S. S Mittal, J Niemeijer, JP Schäfer, T Brox - arXiv preprint arXiv:2302.04075, 2023 - arxiv.org GSID: VT5tn8CvcX0J
A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions. Schenck W. A Tharwat, W Schenck - Mathematics, 2023 - mdpi.com GSID: CfPq3KP9WlkJ
Predicting students at risk of dropout in technical course using LMS logs. Giusti R, Netto JFM, Tamada MM. MM Tamada, R Giusti, JFM Netto - Electronics, 2022 - mdpi.com GSID: HxLrOvYNrVcJ
