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Outputs (27)

TouchEnc: a Novel Behavioural Encoding Technique to Enable Computer Vision for Continuous Smartphone User Authentication (2023)
Conference Proceeding
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (in press). TouchEnc: a Novel Behavioural Encoding Technique to Enable Computer Vision for Continuous Smartphone User Authentication.

We are increasingly required to prove our identity when using smartphones through explicit authentication processes such as passwords or physiological biometrics, e.g., authorising online banking transactions or unlocking smartphones. However, these... Read More about TouchEnc: a Novel Behavioural Encoding Technique to Enable Computer Vision for Continuous Smartphone User Authentication.

An omnidirectional approach to touch-based continuous authentication (2023)
Journal Article
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2023). An omnidirectional approach to touch-based continuous authentication. Computers and Security, 128, Article 103146. https://doi.org/10.1016/j.cose.2023.103146

This paper focuses on how touch interactions on smartphones can provide a continuous user authentication service through behaviour captured by a touchscreen. While efforts are made to advance touch-based behavioural authentication, researchers often... Read More about An omnidirectional approach to touch-based continuous authentication.

CAPE: Context-Aware Private Embeddings for Private Language Learning (2021)
Conference Proceeding
Plant, R., Gkatzia, D., & Giuffrida, V. (2021). CAPE: Context-Aware Private Embeddings for Private Language Learning. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (7970-7978)

Neural language models have contributed to state-of-the-art results in a number of downstream applications including sentiment analysis, intent classification and others. However, obtaining text representations or embeddings using these models risks... Read More about CAPE: Context-Aware Private Embeddings for Private Language Learning.

Semi-Supervised Domain Adaptation for Holistic Counting under Label Gap (2021)
Journal Article
Litrico, M., Battiato, S., Tsaftaris, S. A., & Giuffrida, M. V. (2021). Semi-Supervised Domain Adaptation for Holistic Counting under Label Gap. Journal of Imaging, 7(10), Article 198. https://doi.org/10.3390/jimaging7100198

This paper proposes a novel approach for semi-supervised domain adaptation for holistic regression tasks, where a DNN predicts a continuous value y∈R given an input image x. The current literature generally lacks specific domain adaptation approaches... Read More about Semi-Supervised Domain Adaptation for Holistic Counting under Label Gap.

Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses (2021)
Conference Proceeding
Frangulea, M., Pantos, C., Giuffrida, V., & Valente, J. (2021). Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses. In Precision agriculture ’21 (493-500). https://doi.org/10.3920/978-90-8686-916-9_59

A tool for plant phenotyping is proposed to aid users in analyzing data on-demand. This tool is web-based and runs deep learning models. The current study focuses on the development of this tool, as well as obtaining a plant dataset to train a neural... Read More about Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses.

Towards Continuous User Authentication Using Personalised Touch-Based Behaviour (2020)
Conference Proceeding
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2020). Towards Continuous User Authentication Using Personalised Touch-Based Behaviour. In 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00023

In this paper, we present an empirical evaluation of 30 features used in touch-based continuous authentication. It is essential to identify the most significant features for each user, as behaviour is different amongst humans. Thus, a fixed feature s... Read More about Towards Continuous User Authentication Using Personalised Touch-Based Behaviour.

Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants (2020)
Journal Article
Bontpart, T., Concha, C., Giuffrida, V., Robertson, I., Admkie, K., Degefu, T., …Doerner, P. (2020). Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants. Plant Journal, 103(6), 2330-2343. https://doi.org/10.1111/tpj.14877

The phenotypic analysis of root system growth is important to inform efforts to enhance plant resource acquisition from soils. However, root phenotyping still remains challenging due to soil opacity, requiring systems that facilitate root system visi... Read More about Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants.

Understanding Deep Neural Networks For Regression In Leaf Counting (2020)
Conference Proceeding
Dobrescu, A., Giuffrida, M. V., & Tsaftaris, S. A. (2020). Understanding Deep Neural Networks For Regression In Leaf Counting. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (4321-4329). https://doi.org/10.1109/CVPRW.2019.00316

Deep learning methods are constantly increasing in popularity and success across a wide range of computer vision applications. However, they are perceived as 'black boxes', due to the lack of an intuitive interpretation of their decision processes. W... Read More about Understanding Deep Neural Networks For Regression In Leaf Counting.