Marcos Egea‐Cortines

Universidad Politécnica de Cartagena

Papers

1

Total Citations

19

H-Index

1

About

Dr. Marcos Egea‐Cortines is a pioneering researcher at the intersection of plant molecular biology and artificial intelligence. His work primarily focuses on the genetic regulation of floral development, circadian rhythms, and the application of deep learning to agricultural imaging. A major contribution is his development of 3DeepM, an ad hoc deep learning architecture for multispectral image classification, which dramatically reduces computational costs by using far fewer parameters than traditional models—making advanced AI accessible for experimental and field-based agricultural setups. This work, published in 2021 and garnering 19 citations, exemplifies his drive to bridge cutting-edge computational methods with practical biological challenges. Beyond this, Dr. Egea‐Cortines has made foundational discoveries in the molecular mechanisms controlling flower shape and scent, integrating genomics with phenomics. His interdisciplinary approach has not only advanced fundamental plant science but also provided scalable tools for precision agriculture. For students and researchers, his career demonstrates how marrying deep learning with plant biology can unlock new efficiencies in crop monitoring and genetic understanding, all while maintaining a focus on real-world applicability.

Research Focus

Key Achievements

1
H-Index
1
Papers
19
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
3DeepM: An Ad Hoc Architecture Based on Deep Learning Methods for Multispectral Image Classification
19 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Universidad Politécnica de Cartagena

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago