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No-reference synthetic image quality assessment with convolutional neural network and local image saliency (2019)
Journal Article
Wang, X., Liang, X., Yang, B., & Li, F. W. (2019). No-reference synthetic image quality assessment with convolutional neural network and local image saliency. Computational Visual Media, 5(2), 193-208. https://doi.org/10.1007/s41095-019-0131-6

Depth-image-based rendering (DIBR) is widely used in 3DTV, free-viewpoint video, and interactive 3D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, particularly geometric distortions... Read More about No-reference synthetic image quality assessment with convolutional neural network and local image saliency.

INRFlow: An interconnection networks research flow-level simulation framework (2019)
Journal Article
Navaridas, J., Pascual, J. A., Erickson, A., Stewart, I. A., & Luján, M. (2019). INRFlow: An interconnection networks research flow-level simulation framework. Journal of Parallel and Distributed Computing, 130, 140-152. https://doi.org/10.1016/j.jpdc.2019.03.013

This paper presents INRFlow, a mature, frugal, flow-level simulation framework for modelling large-scale networks and computing systems. INRFlow is designed to carry out performance-related studies of interconnection networks for both high performanc... Read More about INRFlow: An interconnection networks research flow-level simulation framework.

Edge Computing-Based Security Framework for Big Data Analytics in VANETs (2019)
Journal Article
Garg, S., Singh, A., Kaur, K., Aujla, G. S., Batra, S., Kumar, N., & Obaidat, M. (2019). Edge Computing-Based Security Framework for Big Data Analytics in VANETs. IEEE Network, 33(2), 72-81. https://doi.org/10.1109/mnet.2019.1800239

With the exponential growth of technologies such as IoT, edge computing, and 5G, a tremendous amount of structured and unstructured data is being generated from different applications in the smart citiy environment in recent years. Thus, there is a n... Read More about Edge Computing-Based Security Framework for Big Data Analytics in VANETs.

Max-flow min-cut theorems on dispersion and entropy measures for communication networks (2019)
Journal Article
Riis, S., & Gadouleau, M. (2019). Max-flow min-cut theorems on dispersion and entropy measures for communication networks. Information and Computation, 267, 49-73. https://doi.org/10.1016/j.ic.2019.03.004

The paper presents four distinct new ideas and results for communication networks: 1) We show that relay-networks (i.e. communication networks where different nodes use the same coding functions) can be used to model dynamic networks, in a way, vague... Read More about Max-flow min-cut theorems on dispersion and entropy measures for communication networks.

On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-based Bio-Signal Decoding in BCI Speller Applications (2019)
Journal Article
Podmore, J., Breckon, T., Aznan, N., & Connolly, J. (2019). On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-based Bio-Signal Decoding in BCI Speller Applications. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(4), 611-618. https://doi.org/10.1109/tnsre.2019.2904791

Brain-computer interfaces (BCI) harnessing Steady State Visual Evoked Potentials (SSVEP) manipulate the frequency and phase of visual stimuli to generate predictable oscillations in neural activity. For BCI spellers, oscillations are matched with alp... Read More about On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-based Bio-Signal Decoding in BCI Speller Applications.

Algorithms for outerplanar graph roots and graph roots of pathwidth at most 2 (2019)
Journal Article
Golovach, P., Heggernes, P., Kratch, D., Lima, P., & Paulusma, D. (2019). Algorithms for outerplanar graph roots and graph roots of pathwidth at most 2. Algorithmica, 81(7), 2795-2828. https://doi.org/10.1007/s00453-019-00555-y

Deciding if a graph has a square root is a classical problem, which has been studied extensively both from graph-theoretic and algorithmic perspective. As the problem is NP-complete, substantial effort has been dedicated to determining the complexity... Read More about Algorithms for outerplanar graph roots and graph roots of pathwidth at most 2.

Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers (2019)
Journal Article
Gao, Y., Long, Y., Guan, Y., Basu, A., Baggaley, J., & Ploetz, T. (2019). Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 3(1), Article 12. https://doi.org/10.1145/3314399

Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtl's General Movement Assessment (GMA) can be used to classify inf... Read More about Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers.

Generative Adversarial Framework for Depth Filling via Wasserstein Metric, Cosine Transform and Domain Transfer (2019)
Journal Article
Atapour-Abarghouei, A., Akcay, S., de La Garanderie, G. P., & Breckon, T. P. (2019). Generative Adversarial Framework for Depth Filling via Wasserstein Metric, Cosine Transform and Domain Transfer. Pattern Recognition, 91, 232-244. https://doi.org/10.1016/j.patcog.2019.02.010

In this work, the issue of depth filling is addressed using a self-supervised feature learning model that predicts missing depth pixel values based on the context and structure of the scene. A fully-convolutional generative model is conditioned on th... Read More about Generative Adversarial Framework for Depth Filling via Wasserstein Metric, Cosine Transform and Domain Transfer.

Temporal flows in temporal networks (2019)
Journal Article
Akrida, E. C., Czyzowicz, J., Gąsieniec, L., Kuszner, Ł., & Spirakis, P. G. (2019). Temporal flows in temporal networks. Journal of Computer and System Sciences, 103, 46-60. https://doi.org/10.1016/j.jcss.2019.02.003

We introduce temporal flows on temporal networks. We show that one can find the maximum amount of flow that can pass from a source vertex s to a sink vertex t up to a given time in Polynomial time. We provide a static Time-Extended network (TEG) of p... Read More about Temporal flows in temporal networks.