Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses
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 devel...
Leveraging multiple datasets for deep leaf counting
Conference Proceeding
Dobrescu, A., Giuffrida, M. V., & Tsaftaris, S. A. (2018)
Leveraging multiple datasets for deep leaf counting. https://doi.org/10.1109/ICCVW.2017.243
The number of leaves a plant has is one of the key traits (phenotypes) describing its development and growth. Here, we propose an automated, deep learning based approach for c...
Towards Continuous User Authentication Using Personalised Touch-Based Behaviour
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 e...
CAPE: Context-Aware Private Embeddings for Private Language Learning
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. Howe...
An interactive tool for semi-automated leaf annotation
Conference Proceeding
Minervini, M., Giuffrida, M. V., & Tsaftaris, S. (2015)
An interactive tool for semi-automated leaf annotation. In Proceedings of the Computer Vision Problems in Plant Phenotyping Workshop 2015, (6.1-6.13). https://doi.org/10.5244/c.29.cvppp.6
High throughput plant phenotyping is emerging as a necessary step towards meeting agricultural demands of the future. Central to its success is the development of robust compu...
Root Gap Correction with a Deep Inpainting Model
Conference Proceeding
Chen, H., Giuffrida, M. V., Doerner, P., & Tsaftaris, S. A. (2018)
Root Gap Correction with a Deep Inpainting Model
Imaging roots of growing plants in a non-invasive and affordable fashion has been a long-standing problem in image-assisted plant breeding and phenotyping. One of the most aff...
Leaf Counting Without Annotations Using Adversarial Unsupervised Domain Adaptation
Conference Proceeding
Giuffrida, M. V., Dobrescu, A., Doerner, P., & Tsaftaris, S. A. (2019)
Leaf Counting Without Annotations Using Adversarial Unsupervised Domain Adaptation
Deep learning is making strides in plant phenotyping and agriculture. But pretrained models require significant adaptation to work on new target datasets originating from a di...
Whole Image Synthesis Using a Deep Encoder-Decoder Network
Conference Proceeding
Sevetlidis, V., Giuffrida, M. V., & Tsaftaris, S. A. (2016)
Whole Image Synthesis Using a Deep Encoder-Decoder Network. In Simulation and Synthesis in Medical Imaging. , (127-137). https://doi.org/10.1007/978-3-319-46630-9_13
The synthesis of medical images is an intensity transformation of a given modality in a way that represents an acquisition with a different modality (in the context of MRI thi...
Adversarial Large-scale Root Gap Inpainting
Conference Proceeding
Chen, H., Giuffrida, M. V., Doerner, P., & Tsaftaris, S. A. (2019)
Adversarial Large-scale Root Gap Inpainting
Root imaging of a growing plant in a non-invasive, affordable , and effective way remains challenging. One approach is to image roots by growing them in a rhizobox, a soil-fil...
On Blind Source Camera Identification
Conference Proceeding
Farinella, G. M., Giuffrida, M. V., Digiacomo, V., & Battiato, S. (2015)
On Blind Source Camera Identification. In Advanced Concepts for Intelligent Vision Systems. , (464-473). https://doi.org/10.1007/978-3-319-25903-1_40
An interesting and challenging problem in digital image forensics is the identification of the device used to acquire an image. Although the source imaging device can be retri...