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A Quick Review of Deep Learning Algorithms and Architectures

@Machine_learn
🛠 ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Github: https://github.com/jiacheng-ye/zerogen

Paper: https://arxiv.org/abs/2202.07922v1

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

@Machine_learn
Uniformer: Unified Transformer for Efficient Spatiotemporal Representation Learning

Github: https://github.com/sense-x/uniformer

Paper: https://arxiv.org/abs/2201.04676v1

Tasks: https://paperswithcode.com/dataset/kinetics-600

@Machine_learn
20191119_Ahmadi_2.pdf
26.4 MB
EEG microstate and functional brain network features for
classification of epilepsy and PNES #EEG #Thesis @Machine_learn
electronics-10-03037.pdf
2.5 MB
A Survey on EEG Signal Processing Techniques and Machine
Learning: Applications to the Neurofeedback of
Autobiographical Memory Deficits in Schizophrenia #EEG #ML #DL @Machine_learn
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
When the code works anyway



♥️😂 @Machine_learn
2025/07/04 16:20:11
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