Domenico D. Bloisi

About

Domenico D. Bloisi is a computer scientist whose research sits at the intersection of robotics, computer vision, and machine learning, with particular emphasis on precision agriculture and human-robot interaction. He is perhaps best known for his pioneering work on crop and weed segmentation, where his context-independent pixel-wise segmentation approach (2019, 124 citations) and multi-spectral image synthesis methods (2021, 110 citations) have significantly advanced the capacity of agricultural robots to distinguish crops from weeds in real time. His use of generative adversarial networks for data augmentation in farming applications further demonstrates his commitment to solving practical data scarcity challenges in the field. Beyond agriculture, Bloisi has made meaningful contributions to semantic mapping and environmental knowledge acquisition, enabling robots to represent and interact with everyday surroundings more naturally. His work on embedded GPU optimization for ORB-SLAM and CNN-based peg-in-hole assembly reflects a strong engineering sensibility, bridging theoretical deep learning with real-world robotic deployment. He has also explored robot cybersecurity and anomaly detection—an increasingly vital frontier. With nearly 500 cumulative citations across diverse domains, Bloisi's body of work represents a coherent and impactful vision for intelligent, autonomous robotic systems operating in complex, real-world environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Crop and Weeds Classification for Precision Agriculture Using Context-Independent Pixel-Wise Segmentation

   124 citations · 2019
2. 2
   Multi-Spectral Image Synthesis for Crop/Weed Segmentation in Precision Farming

   110 citations · 2021
3. 3
   A Deep Learning Approach for Object Recognition with NAO Soccer Robots

   48 citations · 2017
4. 4
   Living with robots: Interactive environmental knowledge acquisition

   41 citations · 2016
5. 5
   Data Augmentation Using GANs for Crop/Weed Segmentation in Precision Farming

   40 citations · 2020
6. 6
   On-line semantic mapping

   37 citations · 2013
7. 7
   Data Flow ORB-SLAM for Real-time Performance on Embedded GPU Boards

   32 citations · 2019
8. 8
   Peg-in-Hole Using 3D Workpiece Reconstruction and CNN-based Hole Detection

   31 citations · 2020
9. 9
   A Comparative Analysis on the use of Autoencoders for Robot Security Anomaly Detection

   18 citations · 2019
10. 10
    Automatic Extraction of Structural Representations of Environments

    17 citations · 2015

Key Collaborators

Contact & Links