Skip to main content

Research Repository

Advanced Search

Outputs (199)

Musical Genre Recognition Based on Deep Descriptors of Harmony, Instrumentation, and Segments (2023)
Presentation / Conference Contribution
Vatolkin, I., Gotham, M., Lόpez, N. N., & Ostermann, F. (2023, April). Musical Genre Recognition Based on Deep Descriptors of Harmony, Instrumentation, and Segments. Presented at EvoMUSART 2023: Artificial Intelligence in Music, Sound, Art and Design, Brno, Czech Republic

Deep learning has recently established itself as a cluster of methods of choice for almost all classification tasks in music information retrieval. However, despite very good classification performance, it sometimes brings disadvantages including lon... Read More about Musical Genre Recognition Based on Deep Descriptors of Harmony, Instrumentation, and Segments.

Focalized Contrastive View-invariant Learning for Self-supervised Skeleton-based Action Recognition (2023)
Journal Article
Men, Q., Ho, E. S., Shum, H. P., & Leung, H. (2023). Focalized Contrastive View-invariant Learning for Self-supervised Skeleton-based Action Recognition. Neurocomputing, 537, 198-209. https://doi.org/10.1016/j.neucom.2023.03.070

Learning view-invariant representation is a key to improving feature discrimination power for skeleton-based action recognition. Existing approaches cannot effectively remove the impact of viewpoint due to the implicit view-dependent representations.... Read More about Focalized Contrastive View-invariant Learning for Self-supervised Skeleton-based Action Recognition.

Smart Community Networks and Systems (2023)
Journal Article
Tu, W., Simeonidou, D., Wang, L., Hua, X., Choi, B., & Han, R. (2023). Smart Community Networks and Systems. IEEE Network, 37(2), 126-126. https://doi.org/10.1109/mnet.2023.10239368

Community networks and systems were started as non-profitable last-mile access networks that were operated within local communities, sometimes even without access to the public Internet. They are established and maintained by communities to enhance c... Read More about Smart Community Networks and Systems.

Generalized Zero-Shot Domain Adaptation via Coupled Conditional Variational Autoencoders (2023)
Journal Article
Wang, Q., & Breckon, T. (2023). Generalized Zero-Shot Domain Adaptation via Coupled Conditional Variational Autoencoders. Neural Networks, 163, 40-52. https://doi.org/10.1016/j.neunet.2023.03.033

Domain adaptation aims to exploit useful information from the source domain where annotated training data are easier to obtain to address a learning problem in the target domain where only limited or even no annotated data are available. In classific... Read More about Generalized Zero-Shot Domain Adaptation via Coupled Conditional Variational Autoencoders.

Realism versus Performance for Adversarial Examples Against DL-based NIDS (2023)
Presentation / Conference Contribution
Alatwi, H. A., & Morisset, C. (2023, March). Realism versus Performance for Adversarial Examples Against DL-based NIDS. Presented at SAC '23: 38th ACM/SIGAPP Symposium on Applied Computing, Tallinn Estonia

The application of deep learning-based (DL) network intrusion detection systems (NIDS) enables effective automated detection of cyberattacks. Such models can extract valuable features from high-dimensional and heterogeneous network traffic with minim... Read More about Realism versus Performance for Adversarial Examples Against DL-based NIDS.

Computational graphs for matrix functions (2023)
Journal Article
Jarlebring, E., Fasi, M., & Ringh, E. (2023). Computational graphs for matrix functions. ACM Transactions on Mathematical Software, 48(4), 1-35. https://doi.org/10.1145/3568991

Many numerical methods for evaluating matrix functions can be naturally viewed as computational graphs. Rephrasing these methods as directed acyclic graphs (DAGs) is a particularly effective approach to study existing techniques, improve them, and ev... Read More about Computational graphs for matrix functions.

Atmospheric optical turbulence analysis in London’s financial district (2023)
Presentation / Conference Contribution
Westerby-Griffin, L., Osborn, J., Farley, O. J. D., Griffiths, R., & Love, G. D. (2023, January). Atmospheric optical turbulence analysis in London’s financial district. Presented at Free-Space Laser Communications XXXV, San Francisco, United States

Atmospheric optical turbulence causes signal loses in laser propagation. Here we present vertical measurements of optical turbulence taken in London’s financial district. Additionally, we demonstrate a method of modelling atmospheric states in simula... Read More about Atmospheric optical turbulence analysis in London’s financial district.

Induced Disjoint Paths and Connected Subgraphs for H-Free Graphs (2023)
Journal Article
Martin, B., Paulusma, D., Smith, S., & van Leeuwen, E. J. (2023). Induced Disjoint Paths and Connected Subgraphs for H-Free Graphs. Algorithmica, 85, 2580–2604. https://doi.org/10.1007/s00453-023-01109-z

Paths P1,…,Pk in a graph G=(V,E) are mutually induced if any two distinct Pi and Pj have neither common vertices nor adjacent vertices. The INDUCED DISJOINT PATHS problem is to decide if a graph G with k pairs of specified vertices (si,ti) contains k... Read More about Induced Disjoint Paths and Connected Subgraphs for H-Free Graphs.