A. Schlageter-Tello
Papers
1
Total Citations
30
H-Index
1
About
Andrés Schlageter-Tello is a researcher whose work lies at the intersection of precision livestock farming and computer vision. His primary research focuses on developing automated methods for monitoring animal behavior and health, particularly in dairy cattle. His most cited paper, "Comparison of segmentation algorithms for cow contour extraction from natural barn background in side view images" (2013, 30 citations), is a foundational contribution to this field. In this work, he systematically evaluated various image processing techniques to reliably isolate individual cows from complex, real-world barn environments—a critical step for enabling automated health and welfare assessments. This research has provided a practical benchmark for subsequent studies on automated lameness detection and body condition scoring. Schlageter-Tello’s work is notable for its emphasis on robust, field-ready solutions that can operate under the challenging lighting and occlusion conditions of commercial barns. By advancing the accuracy of image segmentation, his contributions have helped pave the way for non-invasive, continuous monitoring systems that improve animal welfare and farm management efficiency.
Research Focus
Key Achievements
Top Papers
- 1