activity
20172026
most citedLearning to flock through reinforcement

59 citations · 213 across the 24 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cond-mat.soft2022★ 5 cited

Shapes and dynamic regimes of a polar active fluid droplet under confinement

Adriano Tiribocchi, Mihir Durve, Marco Lauricella +3

Active droplets are artificial microswimmers built from a liquid dispersion by microfluidic tools and showing self-propelled motion. These systems hold particular interest for mimi…

physics.flu-dyn2022

Machine learning assisted droplet trajectories extraction in dense emulsions and their analysis

Mihir Durve, Adriano Tiribocchi, Andrea Montessori +2

This work analyzes trajectories obtained by YOLO and DeepSORT algorithms of dense emulsion systems simulated by Lattice Boltzmann methods. The results indicate that the individual…

cs.CV2022★ 48 cited

DropTrack -- automatic droplet tracking using deep learning for microfluidic applications

Mihir Durve, Adriano Tiribocchi, Fabio Bonaccorso +5

Deep neural networks are rapidly emerging as data analysis tools, often outperforming the conventional techniques used in complex microfluidic systems. One fundamental analysis fre…

cond-mat.soft2022★ 24 cited

The crucial role of adhesion in the transmigration of active droplets through interstitial orifices

A. Tiribocchi, M. Durve, M. Lauricella +3

Active fluid droplets are a class of soft materials exhibiting autonomous motion sustained by an energy supply. Such systems have been shown to capture motility regimes typical of…

cond-mat.soft2022★ 4 cited

Dynamics of polydisperse multiple emulsions in microfluidic channels

A. Tiribocchi, A. Montessori, M. Durve +3

Multiple emulsions are a class of soft fluid in which small drops are immersed within a larger one and stabilized over long periods of time by a surfactant. We recently showed that…