Shiwen Shen
Papers
2
Total Citations
32
H-Index
2
About
Shiwen Shen is a researcher focused on the intersection of computer vision and precision agriculture, with a particular emphasis on automated livestock monitoring. Their major contribution lies in developing efficient, deep learning-based methods for counting pigs in crowded, real-world farm environments—a task traditionally performed manually, which is both time-consuming and error-prone. Shen’s most cited work, "Efficient Pig Counting in Crowds with Keypoints Tracking and Spatial-aware Temporal Response Filtering" (2020), has garnered 29 citations, highlighting its impact on the field. This research advances beyond single-image analysis by integrating keypoint tracking with spatial-temporal filtering to handle occlusions and dynamic crowd movements, significantly improving counting accuracy in video streams. By addressing a critical bottleneck in large-scale pig farming, Shen’s work enables automated, scalable monitoring that reduces labor costs and enhances animal welfare oversight. This achievement positions Shen as a key contributor to the growing domain of AI-driven agricultural technology, offering practical solutions that bridge computer vision research and real-world farming challenges.
Research Focus
Key Achievements
Top Papers
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