1 code implementation • 18 Dec 2023 • Joel L. Lavanchy, Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez, Paolo Fiorini, Beat Muller-Stich, Philipp C. Nett, Jacques Marescaux, Didier Mutter, Nicolas Padoy
The use of multi-centric training data, experiments 6) and 7), improves the generalization capabilities of the models, bringing them beyond the level of independent mono-centric training and validation (experiments 1) and 2)).
no code implementations • 21 Feb 2023 • Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez, Tong Yu, Pietro Mascagni, Didier Mutter, Jacques Marescaux, Paolo Fiorini, Nicolas Padoy
In this work, we propose to use coarser and easier-to-annotate activity labels, namely phases, as weak supervision to learn step recognition with fewer step annotated videos.
1 code implementation • 2 Aug 2022 • Giovanni Menegozzo, Diego Dall'Alba, Paolo Fiorini
This work introduces two novel public datasets for CD in continuous manufacturing processes.
1 code implementation • 30 Jun 2022 • Ameya Pore, Martina Finocchiaro, Diego Dall'Alba, Albert Hernansanz, Gastone Ciuti, Alberto Arezzo, Arianna Menciassi, Alicia Casals, Paolo Fiorini
Flexible endoscopes for colonoscopy present several limitations due to their inherent complexity, resulting in patient discomfort and lack of intuitiveness for clinicians.
no code implementations • 24 Feb 2021 • Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez, Tong Yu, Pietro Mascagni, Didier Mutter, Jacques Marescaux, Paolo Fiorini, Nicolas Padoy
Conclusion: In this work, we present a multi-task multi-stage temporal convolutional network for surgical activity recognition, which shows improved results compared to single-task models on the Bypass40 gastric bypass dataset with multi-level annotations.