Releases: YijianZhou/LoSAR
Releases · YijianZhou/LoSAR
LoSAR
LoSAR
Add location module
SAR_TED
- better default values, especially for glitch removal
- adaptive neg_ratio (one less param in config)
SAR_TED
- Add self-attention after RNN, thus the model is now named as "Self-Attention RNN (SAR)"
- Modify neg-cut strategy, high-assoc sta-date pairs are weighted down, so that is more suitable for intense sequences
- Add glitch removal algorithm to realize higher stability
- More suitable default parameters, should have ~2.75*PAL detection number
RSeL_TED
Use RNN for Sequence Labelling (RSeL). The RSeL model is trained under TED workflow, with PAL detections. RSeL output P&S probability, as most AI pickers do. The RSeL picks can be associated and located with PAL toolkit
CERP_TED
Bug fixed
CERP_TED
- New name: Training-base Earthquake Detection (TED) workflow;
- New CNN model: ResNet style;
- New training sampling method: use unassociated PAL picks as Glitch (the second kind of noise), which is suitable for interseismic period
CERP_Pytorch
Better usage; bug fixed
CERP_Pytorch
Major updates to realize an easy usage
CERP_Pytorch
Better naming; fix dtype bug (exist for certain python or pytorch versions)