Enrico Bellocchio — accepted AI-conference papers

2020

Combining Domain Adaptation and Spatial Consistency for Unseen Fruits Counting: A Quasi-Unsupervised Approach

Enrico Bellocchio, Gabriele Costante, Silvia Cascianelli, Mario Luca Fravolini, Paolo Valigi

RA-L 2020

Autonomous robotic platforms can be effectively used to perform automatic fruits yield estimation. To this aim, robots need data-driven models that process image streams and count, even approximately, the number of fruits in an orchard. However, training such models following a supervised paradigm i

Cited by 33 Source ↗Scholar ↗

2019

Weakly Supervised Fruit Counting for Yield Estimation Using Spatial Consistency

Enrico Bellocchio, Thomas A. Ciarfuglia, Gabriele Costante, Paolo Valigi

RA-L 2019

Fruit counting is a fundamental component for yield estimation applications. Most of the existing approaches address this problem by relying on fruit models (i.e., by using object detectors) or by explicitly learning to count. Despite the impressive results achieved by these approaches, all of them

Cited by 50 Source ↗Scholar ↗