Tiago Cerveira Padilha

Institute for Systems Engineering and Computers

Papers

Total Citations

H-Index

About

Tiago Cerveira Padilha is a researcher whose work sits at the intersection of deep learning, agricultural robotics, and computer vision. His most recognized contribution, "Tomato Detection Using Deep Learning for Robotics Application" (2021), has garnered 5 citations, establishing a foundation for applying convolutional neural networks to precision agriculture. In this work, Padilha demonstrates how state-of-the-art object detection models can be adapted for real-time fruit identification in unstructured field environments—a critical step toward automating harvesting and yield estimation. His research addresses the practical challenges of deploying AI in agriculture, including variable lighting, occlusions, and the need for lightweight models that run on embedded robotic systems. By focusing on a specific, high-value crop, Padilha provides a replicable framework for similar detection tasks in horticulture. His contributions are particularly relevant for students and engineers developing cost-effective, vision-based solutions for sustainable farming. As the demand for agricultural automation grows, Padilha’s work offers a clear, applied example of how deep learning can bridge the gap between lab-based algorithms and real-world robotic applications.