Papers

2

Total Citations

14

H-Index

2

About

Marine Clogenson’s research sits at the intersection of biologically inspired computer vision and robotics, focusing on how robots can perceive and interpret their environment more naturally. Her major contributions center on developing novel approaches for feature extraction from both intensity and range images—key for 3D object recognition and robotic navigation. In her 2013 work, she introduced a biologically inspired method for extracting features from low-cost 3D cameras, advancing the use of RGB-D data in real-world robotics. Her 2012 paper proposed a groundbreaking robot vision system combining hexagonal grid structures with spiking neural networks, mimicking the human visual cortex to improve segmentation accuracy in range images. Though her citation counts (7 each) reflect a focused, emerging impact, these works are foundational in bridging neural computation and practical robot perception. Clogenson’s research is notable for its interdisciplinary ambition—merging neuroscience, computer vision, and robotics—and offers a compelling blueprint for developing more adaptive, human-like machine vision systems. Her work remains a valuable reference for students and researchers exploring bio-inspired sensing and autonomous navigation.

Research Focus

Key Achievements

2
H-Index
2
Papers
14
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Biologically inspired intensity and range image feature extraction
7 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of Ulster, École d'Ingénieurs en Chimie et Sciences du Numérique

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago