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Found 6 papers, 2 papers with code
Large-Scale Video Analytics through Object-Level Consolidation
As the number of installed cameras grows, so do the compute resources required to process and analyze all the images captured by these cameras.
Towards Automatic Model Specialization for Edge Video Analytics
In this paper, we present and evaluate COVA (Contextually Optimized Video Analytics), a framework to assist in the automatic specialization of models for video analytics in edge cameras.
Improving Maritime Traffic Emission Estimations on Missing Data with CRBMs
Unfortunately, these models are sensitive to missing or corrupted data, and therefore they need data curation techniques to significantly improve the estimation accuracy.
Sequence-to-sequence models for workload interference
In this work we propose a methodology for modeling co-scheduling of jobs on data-centers, based on their behavior towards resources and execution time, using sequence-to-sequence models based on recurrent neural networks.
ALOJA: A Framework for Benchmarking and Predictive Analytics in Big Data Deployments
This article presents the ALOJA project and its analytics tools, which leverages machine learning to interpret Big Data benchmark performance data and tuning.
ALOJA-ML: A Framework for Automating Characterization and Knowledge Discovery in Hadoop Deployments
Hadoop presents a complex execution environment, where costs and performance depends on a large number of software (SW) configurations and on multiple hardware (HW) deployment choices.
