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All Outputs (11)

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.

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.

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.

Doing More With Less: A Multitask Deep Learning Approach in Plant Phenotyping (2020)
Journal Article
Dobrescu, A., Giuffrida, M. V., & Tsaftaris, S. A. (2020). Doing More With Less: A Multitask Deep Learning Approach in Plant Phenotyping. Frontiers in Plant Science, 11, Article 141. https://doi.org/10.3389/fpls.2020.00141

Image-based plant phenotyping has been steadily growing and this has steeply increased the need for more efficient image analysis techniques capable of evaluating multiple plant traits. Deep learning has shown its potential in a multitude of visual t... Read More about Doing More With Less: A Multitask Deep Learning Approach in Plant Phenotyping.

Unsupervised Rotation Factorization in Restricted Boltzmann Machines (2019)
Journal Article
Giuffrida, M. V., & Tsaftaris, S. A. (2020). Unsupervised Rotation Factorization in Restricted Boltzmann Machines. IEEE Transactions on Image Processing, 29(1), 2166-2175. https://doi.org/10.1109/TIP.2019.2946455

Finding suitable image representations for the task at hand is critical in computer vision. Different approaches extending the original Restricted Boltzmann Machine (RBM) model have recently been proposed to offer rotation-invariant feature learning.... Read More about Unsupervised Rotation Factorization in Restricted Boltzmann Machines.

Pheno-Deep Counter: a unified and versatile deep learning architecture for leaf counting (2018)
Journal Article
Giuffrida, M. V., Doerner, P., & Tsaftaris, S. A. (2018). Pheno-Deep Counter: a unified and versatile deep learning architecture for leaf counting. Plant Journal, 96(4), 880-890. https://doi.org/10.1111/tpj.14064

Direct observation of morphological plant traits is tedious and a bottleneck for high‐throughput phenotyping. Hence, interest in image‐based analysis is increasing, with the requirement for software that can reliably extract plant traits, such as lea... Read More about Pheno-Deep Counter: a unified and versatile deep learning architecture for leaf counting.

Citizen crowds and experts: observer variability in image-based plant phenotyping (2018)
Journal Article
Giuffrida, M. V., Chen, F., Scharr, H., & Tsaftaris, S. A. (2018). Citizen crowds and experts: observer variability in image-based plant phenotyping. Plant Methods, 14(1), Article 12 (2018). https://doi.org/10.1186/s13007-018-0278-7

Background: Image-based plant phenotyping has become a powerful tool in unravelling genotype–environment interactions. The utilization of image analysis and machine learning have become paramount in extracting data stemming from phenotyping experime... Read More about Citizen crowds and experts: observer variability in image-based plant phenotyping.

Multimodal MR Synthesis via Modality-Invariant Latent Representation (2017)
Journal Article
Chartsias, A., Joyce, T., Giuffrida, M. V., & Tsaftaris, S. A. (2018). Multimodal MR Synthesis via Modality-Invariant Latent Representation. IEEE Transactions on Medical Imaging, 37(3), 803-814. https://doi.org/10.1109/tmi.2017.2764326

We propose a multi-input multi-output fully convolutional neural network model for MRI synthesis. The model is robust to missing data, as it benefits from, but does not require, additional input modalities. The model is trained end-to-end, and learns... Read More about Multimodal MR Synthesis via Modality-Invariant Latent Representation.

Phenotiki: an open software and hardware platform for affordable and easy image-based phenotyping of rosette-shaped plants (2017)
Journal Article
Minervini, M., Giuffrida, M. V., Perata, P., & Tsaftaris, S. A. (2017). Phenotiki: an open software and hardware platform for affordable and easy image-based phenotyping of rosette-shaped plants. Plant Journal, 90(1), 204-216. https://doi.org/10.1111/tpj.13472

Phenotyping is important to understand plant biology, but current solutions are costly, not versatile or are difficult to deploy. To solve this problem, we present Phenotiki, an affordable system for plant phenotyping that, relying on off-the-shelf p... Read More about Phenotiki: an open software and hardware platform for affordable and easy image-based phenotyping of rosette-shaped plants.