Luis Miguel Soria Morillo
Papers
1
Total Citations
10
H-Index
1
About
Luis Miguel Soria Morillo is a researcher whose work lies at the intersection of deep learning, computer vision, and energy-efficient artificial intelligence. His most cited paper, "How efficient deep-learning object detectors are?" (2019, 10 citations), critically evaluates the computational and energy demands of state-of-the-art object detection models, addressing a pressing challenge in deploying AI on resource-constrained devices. This contribution highlights his focus on balancing accuracy with efficiency, a key concern for real-world applications like autonomous systems and mobile computing. Soria Morillo’s research has practical implications for sustainable AI, helping to guide the development of models that are both powerful and environmentally conscious. While his citation count reflects a growing recognition of this work, his broader impact includes advancing methodologies for optimizing deep learning architectures. His efforts contribute to a more accessible and responsible AI landscape, making him a notable voice in the ongoing dialogue about the trade-offs between performance and resource consumption in modern machine learning.
Research Focus
Key Achievements
Top Papers
- 1How efficient deep-learning object detectors are?10 citations · 2019