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Found 2 papers, 1 papers with code
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
By incorporating regular convolutions in the search space and directly optimizing the network architectures for object detection, we obtain a family of object detection models, MobileDets, that achieve state-of-the-art results across mobile accelerators.
Learning from Sparse Datasets: Predicting Concrete's Strength by Machine Learning
Here, based on the analysis of a large dataset (>10, 000 observations) of measured compressive strengths from industrially-produced concretes, we compare the ability of select ML algorithms to "learn" how to reliably predict concrete strength as a function of the size of the dataset.
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