ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2309.08200
  4. Cited By
TF-SepNet: An Efficient 1D Kernel Design in CNNs for Low-Complexity
  Acoustic Scene Classification
v1v2v3v4 (latest)

TF-SepNet: An Efficient 1D Kernel Design in CNNs for Low-Complexity Acoustic Scene Classification

15 September 2023
Yiqian Cai
Peihong Zhang
Shengchen Li
ArXiv (abs)PDFHTML

Papers citing "TF-SepNet: An Efficient 1D Kernel Design in CNNs for Low-Complexity Acoustic Scene Classification"

11 / 11 papers shown
Title
Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs
Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs
Xiaohan Ding
Xinming Zhang
Yi Zhou
Jungong Han
Guiguang Ding
Jian Sun
VLM
151
552
0
13 Mar 2022
Broadcasted Residual Learning for Efficient Keyword Spotting
Broadcasted Residual Learning for Efficient Keyword Spotting
Byeonggeun Kim
Simyung Chang
Jinkyu Lee
Dooyong Sung
100
124
0
08 Jun 2021
Acoustic Scene Classification Based on a Large-margin Factorized CNN
Acoustic Scene Classification Based on a Large-margin Factorized CNN
Janghoon Cho
Sungrack Yun
Hyoungwoo Park
Jungyun Eum
Kyuwoong Hwang
37
13
0
14 Oct 2019
Receptive-field-regularized CNN variants for acoustic scene
  classification
Receptive-field-regularized CNN variants for acoustic scene classification
Khaled Koutini
Hamid Eghbalzadeh
Gerhard Widmer
116
30
0
05 Sep 2019
A multi-device dataset for urban acoustic scene classification
A multi-device dataset for urban acoustic scene classification
A. Mesaros
Toni Heittola
Tuomas Virtanen
43
381
0
25 Jul 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
316
9,811
0
25 Oct 2017
ShuffleNet: An Extremely Efficient Convolutional Neural Network for
  Mobile Devices
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
Xiangyu Zhang
Xinyu Zhou
Mengxiao Lin
Jian Sun
AI4TS
147
6,886
0
04 Jul 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Priya Goyal
Piotr Dollár
Ross B. Girshick
P. Noordhuis
Lukasz Wesolowski
Aapo Kyrola
Andrew Tulloch
Yangqing Jia
Kaiming He
3DH
128
3,685
0
08 Jun 2017
Understanding the Effective Receptive Field in Deep Convolutional Neural
  Networks
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
Wenjie Luo
Yujia Li
R. Urtasun
R. Zemel
HAI
102
1,803
0
15 Jan 2017
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
350
8,179
0
13 Aug 2016
Acoustic Scene Classification
Acoustic Scene Classification
D. Barchiesi
D. Giannoulis
D. Stowell
Mark D. Plumbley
157
406
0
13 Nov 2014
1