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Found 2 papers, 1 papers with code
TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems
This work implements TinySeg on top of the existing tiny machine learning framework and demonstrates that TinySeg can reduce the peak memory usage of an image segmentation model by 39. 3% for tiny embedded systems.
The Geometry of Nonlinear Embeddings in Kernel Discriminant Analysis
We study the geometry of nonlinear embeddings in discriminant analysis with polynomial kernels and Gaussian kernel by identifying the population-level discriminant function that depends on the data distribution and the kernel.
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