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Found 6 papers, 1 papers with code
Camera clustering for scalable stream-based active distillation
We present a scalable framework designed to craft efficient lightweight models for video object detection utilizing self-training and knowledge distillation techniques.
Streamlined Hybrid Annotation Framework using Scalable Codestream for Bandwidth-Restricted UAV Object Detection
Emergency response missions depend on the fast relay of visual information, a task to which unmanned aerial vehicles are well adapted.
Optimal Intermittent Particle Filter
We prove that in terms of expected mean square error, the stochastic program filter outperforms the online filter, which itself outperforms the offline filter.
Solving inverse problems with deep neural networks driven by sparse signal decomposition in a physics-based dictionary
Deep neural networks (DNN) have an impressive ability to invert very complex models, i. e. to learn the generative parameters from a model's output.
Prognostic Power of Texture Based Morphological Operations in a Radiomics Study for Lung Cancer
The importance of radiomics features for predicting patient outcome is now well-established.
Secure Architectures Implementing Trusted Coalitions for Blockchained Distributed Learning (TCLearn)
Distributed learning across a coalition of organizations allows the members of the coalition to train and share a model without sharing the data used to optimize this model.
