Learning Transferable Human Behavior Representations From Sensor Data - Flora Salim

Explore cutting-edge techniques for recognizing human behavior patterns from sensor data in this insightful conference talk. Delve into the challenges of processing sensor information and learn about innovative approaches to representation learning and temporal segmentation. Discover how voice learning and context play crucial roles in behavior recognition, and gain valuable insights into domain adaptation strategies. Understand the complete behavior recognition pipeline, from preprocessing to application, and explore real-world examples that demonstrate the power of transferable human behavior representations.

Introduction
Behavior Recognition Pipeline
Sensor Data Challenges
Representation Learning
Temporal Segmentation
Applications
Preprocessing
Segmentation
Voice Learning
Context
Example
Domain Adaptation
Conclusion
Questions