| bugcrowd/vulnerability-rating-taxonomy |
387 |
|
0 |
0 |
over 2 years ago |
0 |
|
13 |
apache-2.0 |
Python |
| Bugcrowd’s baseline priority ratings for common security vulnerabilities |
| klbouman/hopstools |
38 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
|
Python |
| tools to convert data from the HOPS format |
| harshalmittal4/Hypergradient_variants |
16 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| Improved Hypergradient optimizers, providing better generalization and faster convergence. |
| irecsys/Tutorial_MSRS |
14 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
|
Java |
| Tutorial for Multi-Stakeholder Recommender Systems |
| hughescr/PGE-EV-Rate-Calculator |
10 |
|
0 |
3 |
about 6 years ago |
23 |
August 30, 2019 |
2 |
|
JavaScript |
| Calculate benefit of E9 vs EV rate plans using PG&E Data |
| lbechberger/LearningPsychologicalSpaces |
10 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
other |
Python |
| Learning a mapping from images to psychological similarity spaces with neural networks. |
| FRBNY-TimeSeriesAnalysis/rstarGlobal |
7 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
bsd-3-clause |
MATLAB |
| Michelle-NYX/DreamNet |
6 |
|
0 |
0 |
about 8 years ago |
0 |
|
1 |
other |
Jupyter Notebook |
| CS230 Project: In this project, we investigate and evaluate the performance of the state-of-the-art model for instance segmentation, Mask R-CNN, on the newly-released Mapillary dataset, whose images focus specifically on driving scenes. We transfer the learning results from the pre-trained weights, fine tune the final layers for Mapillary Datasets. The result shows a significant improvement in precision measurements from the baseline, and achieves at a surpassing performance than benchmarks. |
