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Found 6 papers, 3 papers with code
Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation
Wearable sensors enable health researchers to continuously collect data pertaining to the physiological state of individuals in real-world settings.
FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors
Localization is a critical technology for various applications ranging from navigation and surveillance to assisted living.
GDTM: An Indoor Geospatial Tracking Dataset with Distributed Multimodal Sensors
Constantly locating moving objects, i. e., geospatial tracking, is essential for autonomous building infrastructure.
Heteroskedastic Geospatial Tracking with Distributed Camera Networks
Visual object tracking has seen significant progress in recent years.
Learning Graph-Based Priors for Generalized Zero-Shot Learning
The task of zero-shot learning (ZSL) requires correctly predicting the label of samples from classes which were unseen at training time.
Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification
Zero-shot learning (ZSL) is one of the most extreme forms of learning from scarce labeled data.
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