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From Coarse to Fine: Efficient Training for Audio Spectrogram
  Transformers

From Coarse to Fine: Efficient Training for Audio Spectrogram Transformers

16 January 2024
Jiu Feng
Mehmet Hamza Erol
Joon Son Chung
Arda Senocak
ArXivPDFHTML

Papers citing "From Coarse to Fine: Efficient Training for Audio Spectrogram Transformers"

3 / 3 papers shown
Title
MMViT: Multiscale Multiview Vision Transformers
MMViT: Multiscale Multiview Vision Transformers
Yuchen Liu
Natasha Ong
Kaiyan Peng
Bo Xiong
Qifan Wang
...
Madian Khabsa
Kaiyue Yang
David C. Liu
Donald Williamson
Hanchao Yu
ViT
17
4
0
28 Apr 2023
Simple Pooling Front-ends For Efficient Audio Classification
Simple Pooling Front-ends For Efficient Audio Classification
Xubo Liu
Haohe Liu
Qiuqiang Kong
Xinhao Mei
Mark D. Plumbley
Wenwu Wang
35
16
0
03 Oct 2022
HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound
  Classification and Detection
HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection
Ke Chen
Xingjian Du
Bilei Zhu
Zejun Ma
Taylor Berg-Kirkpatrick
Shlomo Dubnov
ViT
114
262
0
02 Feb 2022
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