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experiment with CNN1d + RNN architecture #29
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jakubczakon
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Oct 13, 2018
* added image channel and params to config (#29) * exping * added large kernel matters architecture, renamed stuff, generalized c… (#30) * added large kernel matters architecture, renamed stuff, generalized conv2drelubn block * exping * exping * copied the old ConvBnRelu block to make sure it is easy to finetune old models * reverted main * Depth (#31) * exping * exping * added depth loaders, and depth_excitation layer, adjusted models and callbacks to deal with both * fixed minor issues * exping * merged/refactored * exping * refactored architectures, moved use_depth param to main * added dropout to lkm constructor, dropped my experiment dir definition * Second level (#33) * exping * first stacked unet training * fixed minor typo-bugs * fixed unet naming bug * added stacking preds exploration * dropped redundant imports * adjusted callbacks to work with stacking, added custom to_tensor_stacking * Auxiliary data (#34) * exping * added option to use auxiliary masks * Stacking (#35) * exping * exping * fixed stacking postpro * Stacking (#36) * exping * exping * fixed stacking postpro * exping * added fully convo stacking, fixed minor issues with loader_mode: stacking * Update architectures.py import fix * Update README.md * Update models.py reverted to default (current best) large kernel matters internal_channel_nr * Stacking (#37) Stacking * Stacking depth (#38) * exping * added depth option to stacking model, dropped stacking unet from models * Empty non empty (#39) * exping * added empty vs non empty loaders/models and execution * changed to lovasz loss as default from bce * reverted default callbacks target name
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CNN1d can go both row-wise and column-wise both should be checked but column-wise should be checked first
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