Three-Filters-to-Normal
napkinXC
| Three-Filters-to-Normal | napkinXC | |
|---|---|---|
| 1 | 1 | |
| 95 | 58 | |
| - | - | |
| 1.8 | 6.7 | |
| over 2 years ago | 4 months ago | |
| C++ | C++ | |
| MIT License | MIT License |
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Three-Filters-to-Normal
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[R] Computer Vision for Driving Scene Understanding: from Autonomous Driving to Road Condition Assessment - Link to a free online lecture by the author in comments
git: https://github.com/ruirangerfan/Three-Filters-to-Normal
napkinXC
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Predicting numerical values to a very high accuracy
If you only have 198 possible values then extreme multiclass models might benefit here with better precision and faster convergence. For example probabilistic label trees might have some relevance. Vowpal Wabbit also has specific reductions for extreme multi class problems. Might be worth a try if other alternatives still don't work out.
What are some alternatives?
unsupervised_disparity_map_segmentation - Road Damage Detection Based on Unsupervised Disparity Map Segmentation (T-ITS)
ehsm - An End-to-End Distributed and Scalable Cloud KMS (Key Management System) built on top of Intel SGX enclave-based HSM (Hardware Security Module), aka eHSM.
rethinking_road_reconstruction_pothole_detection - Rethinking Road Surface 3D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation (T-CYB)
hsm - C++ framework library to simplify state-driven code
vowpal_wabbit - Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
tensorflow - An Open Source Machine Learning Framework for Everyone
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration