Ricardo da Silva Torres
Papers
1
Total Citations
2
H-Index
1
About
Ricardo da Silva Torres is a leading researcher at the intersection of computer vision, machine learning, and precision agriculture. His work focuses on developing automated, AI-driven solutions for agricultural monitoring and crop disease detection, with a particular emphasis on potato crop health. In his highly cited 2025 study on the automated detection and localization of potato blackleg, Torres pioneered the use of convolutional neural networks (CNNs) and activation maps to identify diseased plants with remarkable accuracy. This approach replaces labor-intensive manual inspection, significantly reducing time and costs for seed potato lot quality assessment. Although his most prominent paper currently holds 2 citations, its innovative methodology—combining deep learning with agricultural diagnostics—positions it as a foundational contribution to the field. Torres’s research bridges the gap between advanced computational techniques and practical farming needs, offering scalable tools for early disease detection. His work is particularly impactful for researchers and students interested in applied AI, agricultural technology, and sustainable farming practices, demonstrating how state-of-the-art machine learning can transform traditional agricultural workflows.
Research Focus
Key Achievements
Top Papers
- 1