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Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. ...
NESD-Imaging is a 2D rendering framework for Java. It combines JAI and Java2D and extends them by providing lazy rendering (do not block UI). It provides geo-positionned images rendering (à la google-map). It scales well to large image set (>500GB).