Outputs (663)

A Boundary Node Method for path planning of mobile robots (2020)
Journal Article
Saeed, R., Recupero, D. R., & Remagnino, P. (2020). A Boundary Node Method for path planning of mobile robots. Robotics and Autonomous Systems, 123, Article 103320. https://doi.org/10.1016/j.robot.2019.103320

Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling (2020)
Journal Article
Al Moubayed, N., McGough, S., & Awwad Shiekh Hasan, B. (2020). Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling. PeerJ Computer Science, 6, Article e252. https://doi.org/10.7717/peerj-cs.252

The article presents a discriminative approach to complement the unsupervised probabilistic nature of topic modelling. The framework transforms the probabilities of the topics per document into class-dependent deep learning models that extract highly... Read More about Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling.

Cooperative Control of Heterogeneous Connected Vehicle Platoons: An Adaptive Leader-Following Approach (2020)
Journal Article
Hu, J., Bhowmick, P., Arvin, F., Lanzon, A., & Lennox, B. (2020). Cooperative Control of Heterogeneous Connected Vehicle Platoons: An Adaptive Leader-Following Approach. IEEE Robotics and Automation Letters, 5(2), 977-984. https://doi.org/10.1109/lra.2020.2966412

Automatic cruise control of a platoon of multiple connected vehicles in an automated highway system has drawn significant attention of the control practitioners over the past two decades due to its ability to reduce traffic congestion problems, impro... Read More about Cooperative Control of Heterogeneous Connected Vehicle Platoons: An Adaptive Leader-Following Approach.

Multi-scale Feature Fused Single Shot Detector for Small Object Detection in UAV Images (2019)
Presentation / Conference Contribution
Razaak, M., Kerdegari, H., Argyriou, V., & Remagnino, P. (2019, December). Multi-scale Feature Fused Single Shot Detector for Small Object Detection in UAV Images. Presented at COMPUTER VISION SYSTEMS (ICVS 2019)

Generic compact representation through visual-semantic ambiguity removal (2019)
Journal Article
Long, Y., Guan, Y., & Shao, L. (2019). Generic compact representation through visual-semantic ambiguity removal. Pattern Recognition Letters, 117, 186-192. https://doi.org/10.1016/j.patrec.2018.04.024

A General Transductive Regularizer for Zero-Shot Learning (2019)
Presentation / Conference Contribution
Mao, H., Zhang, H., Long, Y., Wang, S., & Yang, L. (2019). A General Transductive Regularizer for Zero-Shot Learning.

Volenti non fit injuria: Ransomware and its Victims (2019)
Presentation / Conference Contribution
Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2019). Volenti non fit injuria: Ransomware and its Victims. . https://doi.org/10.1109/bigdata47090.2019.9006298

With the recent growth in the number of malicious activities on the internet, cybersecurity research has seen a boost in the past few years. However, as certain variants of malware can provide highly lucrative opportunities for bad actors, significan... Read More about Volenti non fit injuria: Ransomware and its Victims.

Colour Processing in Adversarial Attacks on Face Liveness Systems (2019)
Presentation / Conference Contribution
Abduh, L., & Ivrissimtzis, I. (2019). Colour Processing in Adversarial Attacks on Face Liveness Systems. In F. P. Vidal, G. K. . L. Tam, & J. C. Roberts (Eds.), Proceedings of Computer Graphics and Visual Computing 2019 (CGVC) (149-152). https://doi.org/10.2312/cgvc.20191272

In the context of face recognition systems, liveness test is a binary classification task aiming at distinguishing between input images that come from real people’s faces and input images that come from photos or videos of those faces, and presented... Read More about Colour Processing in Adversarial Attacks on Face Liveness Systems.

A King’s Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation (2019)
Presentation / Conference Contribution
Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2019). A King’s Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation. In Proceedings of 2019 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/bigdata47090.2019.9005540

Apparel-based deep learning system design for apparel style recommendation (2019)
Journal Article
Guan, C., Qin, S., & Long, Y. (2019). Apparel-based deep learning system design for apparel style recommendation. International Journal of Clothing Science and Technology, 31(3), 376-389. https://doi.org/10.1108/ijcst-02-2018-0019

Smart Monitoring of Crops Using Generative Adversarial Networks (2019)
Presentation / Conference Contribution
Kerdegari, H., Razaak, M., Argyriou, V., & Remagnino, P. (2019, December). Smart Monitoring of Crops Using Generative Adversarial Networks. Presented at COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2019, PT I Univ Salerno, Dept Comp \& Elect Engn \& Appl Math; SAST Gmbh; A I Tech srl; AI4Health srl; Nexsoft spa; Gesan srl; Hanwha Techwin Europe Ltd; Springer Lecture Notes Comp Sci; Italian Assoc Comp Vi

Adversarial unseen visual feature synthesis for Zero-shot Learning (2019)
Journal Article
Zhang, H., Long, Y., Liu, L., & Shao, L. (2019). Adversarial unseen visual feature synthesis for Zero-shot Learning. Neurocomputing, 329, 12-20. https://doi.org/10.1016/j.neucom.2018.10.043

A Comparison of Embedded Deep Learning Methods for Person Detection (2019)
Presentation / Conference Contribution
Kim, C. E., Oghaz, M. M. D., Fajtl, J., Argyriou, V., & Remagnino, P. (2019). A Comparison of Embedded Deep Learning Methods for Person Detection. In A. Tremeau, G. Farinella, & J. Braz (Eds.), . https://doi.org/10.5220/0007386304590465

Latent Bernoulli Autoencoder (2019)
Presentation / Conference Contribution
Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2019). Latent Bernoulli Autoencoder.

Zero-shot Hashing with orthogonal projection for image retrieval (2019)
Journal Article
Zhang, H., Long, Y., & Shao, L. (2019). Zero-shot Hashing with orthogonal projection for image retrieval. Pattern Recognition Letters, 117, 201-209. https://doi.org/10.1016/j.patrec.2018.04.011

Scene and Environment Monitoring Using Aerial Imagery and Deep Learning (2019)
Presentation / Conference Contribution
Oghaz, M. M., Razaak, M., Kerdegari, H., Argyriou, V., & Remagnino, P. (2019). Scene and Environment Monitoring Using Aerial Imagery and Deep Learning. . https://doi.org/10.1109/dcoss.2019.00078

Learning discriminatory deep clustering models (2019)
Presentation / Conference Contribution
Alqahtani, A., Xie, X., Deng, J., & Jones, M. W. (2019). Learning discriminatory deep clustering models. . https://doi.org/10.1007/978-3-030-29888-3_18

Urban Scene Segmentation using Semi-supervised GAN (2019)
Presentation / Conference Contribution
Kerdegari, H., Razaak, M., Argyriou, V., & Remagnino, P. (2019). Urban Scene Segmentation using Semi-supervised GAN. In L. Bruzzone, F. Bovolo, & J. Benediktsson (Eds.), . https://doi.org/10.1117/12.2533055

Immaculate Depth Perception: Recovering 3D Scene Information via Depth Completion and Prediction (2019)
Thesis
Atapour-Abarghouei, A. (2019). Immaculate Depth Perception: Recovering 3D Scene Information via Depth Completion and Prediction. (Thesis). Durham University. Retrieved from https://durham-repository.worktribe.com/output/1641989

An Integrated Precision Farming Application Based on 5G, UAV and Deep Learning Technologies (2019)
Presentation / Conference Contribution
Razaak, M., Kerdegari, H., Davies, E., Abozariba, R., Broadbent, M., Mason, K., …Remagnino, P. (2019). An Integrated Precision Farming Application Based on 5G, UAV and Deep Learning Technologies. In M. Vento, & G. Percannella (Eds.), . https://doi.org/10.1007/978-3-030-29930-9%5C_11