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Found 4 papers, 1 papers with code
Automated Domain Discovery from Multiple Sources to Improve Zero-Shot Generalization
In this paper, we focus on the challenging problem of multi-source zero shot DG (MDG), where labeled training data from multiple source domains is available but with no access to data from the target domain.
Ranked #19 on
Domain Generalization
on TerraIncognita
Adaptive Subsampling for ROI-based Visual Tracking: Algorithms and FPGA Implementation
Our adaptive subsampling algorithms comprise an object detector and an ROI predictor (Kalman filter) which operate in conjunction to optimize the energy efficiency of the vision pipeline with the end task being object tracking.
Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning
Exploiting known semantic relationships between fine-grained tasks is critical to the success of recent model agnostic approaches.
Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets
We also investigate the impact of dense connections on the extraction process that encourage feature reuse and better gradient flow.
