Emanuele Frontoni
Papers
35
Total Citations
634
H-Index
16
About
Emanuele Frontoni is an Italian researcher whose work spans robotics, computer vision, assistive technology, and precision agriculture — fields united by a commitment to making intelligent systems work meaningfully in the real world. His most cited contributions demonstrate remarkable breadth: from developing monocular vision-based systems that assist visually impaired pedestrians (64 citations) to deploying deep learning-powered mobile robots that autonomously survey retail store shelves (54 citations each), Frontoni consistently bridges cutting-edge machine learning with tangible societal applications. His early work on feature group matching for appearance-based robot localization (2008, 39 citations) established foundational methods still relevant today, while more recent research extends into predictive infrastructure maintenance — including a remote visual inspection system for bridges (33 citations) — and convolutional neural network-based human pose estimation for smart walkers (34 citations). His exploration of UAV-UGV cooperation for extended-range missions and satellite-drone fusion for Agriculture 4.0 further illustrates his systems-level thinking. With contributions touching railway safety robotics, ambient assisted living, and aerial sensing, Frontoni represents a rare interdisciplinary voice whose impact is measurable not only in citations, but in the practical human benefit embedded within each project.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robotic retail surveying by deep learning visual and textual data54 citations · 2019
- 3
- 4Feature group matching for appearance-based localization39 citations · 2008
- 5Satellite and UAV data for Precision Agriculture Applications34 citations · 2019
- 6
- 7A Novel Remote Visual Inspection System for Bridge Predictive Maintenance33 citations · 2022
- 8
- 9
- 10Robotic platform for deep change detection for rail safety and security27 citations · 2017