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Turning old models fashion again: Recycling classical CNN networks using
  the Lattice Transformation

Turning old models fashion again: Recycling classical CNN networks using the Lattice Transformation

28 September 2021
Ana Paula G. S. de Almeida
Flávio de Barros Vidal
ArXivPDFHTML

Papers citing "Turning old models fashion again: Recycling classical CNN networks using the Lattice Transformation"

18 / 18 papers shown
Title
L-CNN: A Lattice cross-fusion strategy for multistream convolutional
  neural networks
L-CNN: A Lattice cross-fusion strategy for multistream convolutional neural networks
Ana Paula G. S. de Almeida
Flávio de Barros Vidal
13
3
0
01 Aug 2020
MMTM: Multimodal Transfer Module for CNN Fusion
MMTM: Multimodal Transfer Module for CNN Fusion
Hamid Reza Vaezi Joze
Amirreza Shaban
Michael L. Iuzzolino
K. Koishida
34
278
0
20 Nov 2019
MFAS: Multimodal Fusion Architecture Search
MFAS: Multimodal Fusion Architecture Search
Juan-Manuel Perez-Rua
Valentin Vielzeuf
S. Pateux
M. Baccouche
F. Jurie
50
178
0
15 Mar 2019
Cross-modal Recurrent Models for Weight Objective Prediction from
  Multimodal Time-series Data
Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data
Petar Velickovic
Laurynas Karazija
Nicholas D. Lane
S. Bhattacharya
Edgar Liberis
Pietro Lio
A. Chieh
O. Bellahsen
M. Vegreville
20
22
0
23 Sep 2017
XFlow: Cross-modal Deep Neural Networks for Audiovisual Classification
XFlow: Cross-modal Deep Neural Networks for Audiovisual Classification
Cătălina Cangea
Petar Velickovic
Pietro Lio
13
30
0
02 Sep 2017
Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition
Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition
Harshala Gammulle
Simon Denman
Sridha Sridharan
Clinton Fookes
44
166
0
04 Apr 2017
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable Convolutions
François Chollet
MDE
BDL
PINN
690
14,454
0
07 Oct 2016
X-CNN: Cross-modal Convolutional Neural Networks for Sparse Datasets
X-CNN: Cross-modal Convolutional Neural Networks for Sparse Datasets
Petar Velickovic
Duo Wang
Nicholas D. Lane
Pietro Lio
38
31
0
01 Oct 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
552
36,599
0
25 Aug 2016
Convolutional Two-Stream Network Fusion for Video Action Recognition
Convolutional Two-Stream Network Fusion for Video Action Recognition
Christoph Feichtenhofer
A. Pinz
Andrew Zisserman
103
2,606
0
22 Apr 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.0K
192,638
0
10 Dec 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal
  Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren
Kaiming He
Ross B. Girshick
Jian Sun
AIMat
ObjD
348
61,900
0
04 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
875
76,547
0
18 May 2015
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
230
43,511
0
17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
655
99,991
0
04 Sep 2014
Two-Stream Convolutional Networks for Action Recognition in Videos
Two-Stream Convolutional Networks for Action Recognition in Videos
Karen Simonyan
Andrew Zisserman
207
7,518
0
09 Jun 2014
Rich feature hierarchies for accurate object detection and semantic
  segmentation
Rich feature hierarchies for accurate object detection and semantic segmentation
Ross B. Girshick
Jeff Donahue
Trevor Darrell
Jitendra Malik
ObjD
174
26,091
0
11 Nov 2013
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
340
7,650
0
03 Jul 2012
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