Francesco Ponzio
Orcid: 0000-0002-8472-8247
According to our database1,
Francesco Ponzio
authored at least 14 papers
between 2017 and 2023.
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Bibliography
2023
W2WNet: A two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality.
Expert Syst. Appl., 2023
Neuro-symbolic Empowered Denoising Diffusion Probabilistic Models for Real-time Anomaly Detection in Industry 4.0.
CoRR, 2023
Robotic Arm Dataset (RoAD): A Dataset to Support the Design and Test of Machine Learning-Driven Anomaly Detection in a Production Line.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023
Neuro-Symbolic Empowered Denoising Diffusion Probabilistic Models for Real-Time Anomaly Detection in Industry 4.0: Wild-and-Crazy-Idea Paper.
Proceedings of the Forum on Specification & Design Languages, 2023
2022
Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations.
BMC Bioinform., 2022
e-Pupil: IoT-Based Augmentative and Alternative Communication Device Exploiting the Pupillary Near-Reflex.
IEEE Access, 2022
2021
Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations: a COVID-19 case-study.
CoRR, 2021
Proceedings of the International Joint Conference on Neural Networks, 2021
2020
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
2019
Int. J. Hum. Comput. Stud., 2019
2018
Proceedings of the Biomedical Engineering Systems and Technologies, 2018
Colorectal Cancer Classification using Deep Convolutional Networks - An Experimental Study.
Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), 2018
2017
A Novel Proof-of-concept Framework for the Exploitation of ConvNets on Whole Slide Images.
Proceedings of the Advances in Intelligent Information Hiding and Multimedia Signal Processing, 2017
A Multi-modal Brain Image Registration Framework for US-guided Neuronavigation Systems - Integrating MR and US for Minimally Invasive Neuroimaging.
Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017), 2017