DeepFusionMOT: A 3D Multi-Object Tracking Framework Based on Camera-LiDAR Fusion with Deep Association

Github: https://github.com/wangxiyang2022/DeepFusionMOT

Paper: https://arxiv.org/abs/2202.12100v1

Dataset: https://paperswithcode.com/dataset/kitti

@Machine_learn

Overcoming catastrophic forgetting in neural networks

Github: https://github.com/ContinualAI/avalanche

Paper: https://arxiv.org/abs/1612.00796v2

Dataset: https://paperswithcode.com/dataset/asc-til-19-tasks

@Machine_learn

When the code works anyway



♥️😂 @Machine_learn

Machine Learning for Mechanical Ventilation Control


http://ai.googleblog.com/2022/02/machine-learning-for-mechanical.html

@Machine_learn

Abstract: SuperpixelGridMasks. It is a data augmentation approach which permits to generate various complementary images from original sensor-based data of varied natures e.g. X-Ray scans, vehicular scenes, people images (see data samples). This approach allows to increase the size of your image-based training datasets towards expecting better performances in your analysis tasks. Experiments have shown that the approach can be efficient for image classification tasks.

Link: https://www.researchgate.net/publication/360062941_SuperpixelGridCut_SuperpixelGridMean_and_SuperpixelGridMix_Data_Augmentation
@Machine_learn

FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

Github: https://github.com/hpcaitech/fastfold

Paper: https://arxiv.org/abs/2203.00854v1

@Machine_learn

Uncertainty Estimation for Heatmap-based Landmark Localization

Github: https://github.com/pykale/pykale

Documentatuin: https://github.com/pykale/pykale

Paper: https://arxiv.org/abs/2203.02351v1

Dataset: https://paperswithcode.com/dataset/kitti

@Machine_learn

https://web.njit.edu/~ym329/dlg_book/dlg_book.pdf

Deep Learning on Graphs

📖 Book

#deeplearning #DL

@Machine_learn

Cryptocurrency liquidity and volatility interrelationships during
the COVID-19 pandemic #Paper @Machine_learn

Periodicity in Cryptocurrency Volatility and Liquidity #Paper @Machine_learn

Deep residual learning for image recognition #paper
@Machine_learn

Alpa: Automated Model-Parallel Deep Learning


http://ai.googleblog.com/2022/05/alpa-automated-model-parallel-deep.html

@Machine_learn

Pix2Seq: A New Language Interface for Object Detection


http://ai.googleblog.com/2022/04/pix2seq-new-language-interface-for.html

@Machine_learn

🔎 Cross-view Transformers for real-time Map-view Semantic Segmentation

Code: https://github.com/bradyz/cross_view_transformers

Paper: https://arxiv.org/abs/2205.02833v1

Dataset: https://paperswithcode.com/dataset/nuscenes

@Machine_learn

Predicting academic performance by considering student heterogeneity #Paper @Machine_learn

An Introduction to Neural
Networks and Deep Learning #Chapter1 @Machine_learn