Giulio Demetrio Perulli

About

Giulio Demetrio Perulli is a researcher at the forefront of precision horticulture and agricultural robotics, specializing in the application of deep learning and computer vision to fruit detection. His major contribution lies in bridging the gap between classical, hard-coded image processing algorithms and modern neural networks for real-time agricultural applications. Perulli’s most impactful work, “Single-Shot Convolution Neural Networks for Real-Time Fruit Detection Within the Tree” (2019), has garnered 165 citations, demonstrating its significance in advancing efficient, real-time fruit detection systems that overcome the computational bottlenecks of traditional methods. This work is pivotal for enabling automated harvesting and yield estimation. Additionally, his comparative study on deep-learning networks versus classical algorithms for apple fruit detection (2020) provides a critical benchmark for the field, guiding future research toward more robust and scalable solutions. Perulli’s research directly supports the development of intelligent agricultural machinery, making him a key figure in the integration of AI into sustainable farming practices.

Research Focus

Key Achievements

Top Papers

1. 1
   Single-Shot Convolution Neural Networks for Real-Time Fruit Detection Within the Tree

   165 citations · 2019
2. 2
   Comparing deep-learning networks for apple fruit detection to classical hard-coded algorithms

   3 citations · 2020

Key Collaborators

Contact & Links