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. 1411.6369
  4. Cited By
Scale-Invariant Convolutional Neural Networks

Scale-Invariant Convolutional Neural Networks

24 November 2014
Yichong Xu
Tianjun Xiao
Jiaxing Zhang
Kuiyuan Yang
Zheng-Wei Zhang
ArXivPDFHTML

Papers citing "Scale-Invariant Convolutional Neural Networks"

18 / 18 papers shown
Title
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations
Andrzej Perzanowski
Tony Lindeberg
45
1
0
17 Sep 2024
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed
  on Orbits
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits
Zhuokai Zhao
Takumi Matsuzawa
W. Irvine
Michael Maire
G. Kindlmann
35
2
0
31 May 2023
Scale-Equivariant UNet for Histopathology Image Segmentation
Scale-Equivariant UNet for Histopathology Image Segmentation
Yi-Lun Yang
S. Dasmahapatra
S. Mahmoodi
20
11
0
10 Apr 2023
Steerable Equivariant Representation Learning
Steerable Equivariant Representation Learning
Sangnie Bhardwaj
Willie McClinton
Tongzhou Wang
Guillaume Lajoie
Chen Sun
Phillip Isola
Dilip Krishnan
OOD
LLMSV
26
5
0
22 Feb 2023
Text2Light: Zero-Shot Text-Driven HDR Panorama Generation
Text2Light: Zero-Shot Text-Driven HDR Panorama Generation
Zhaoxi Chen
Guangcong Wang
Ziwei Liu
90
30
0
20 Sep 2022
Scale dependant layer for self-supervised nuclei encoding
Scale dependant layer for self-supervised nuclei encoding
Peter Naylor
Yao-Hung Hubert Tsai
Marick Laé
Makoto Yamada
SSL
28
0
0
22 Jul 2022
Chaos is a Ladder: A New Theoretical Understanding of Contrastive
  Learning via Augmentation Overlap
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap
Yifei Wang
Qi Zhang
Yisen Wang
Jiansheng Yang
Zhouchen Lin
19
98
0
25 Mar 2022
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Liyao (Mars) Gao
Guang Lin
Wei-wei Zhu
15
8
0
22 Nov 2021
Scale-invariant scale-channel networks: Deep networks that generalise to
  previously unseen scales
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales
Ylva Jansson
T. Lindeberg
11
23
0
11 Jun 2021
DISCO: accurate Discrete Scale Convolutions
DISCO: accurate Discrete Scale Convolutions
Ivan Sosnovik
A. Moskalev
A. Smeulders
18
31
0
04 Jun 2021
Rotation-Invariant Autoencoders for Signals on Spheres
Rotation-Invariant Autoencoders for Signals on Spheres
Suhas Lohit
Shubhendu Trivedi
MDE
22
5
0
08 Dec 2020
Truly shift-invariant convolutional neural networks
Truly shift-invariant convolutional neural networks
Anadi Chaman
Ivan Dokmanić
23
68
0
28 Nov 2020
On Translation Invariance in CNNs: Convolutional Layers can Exploit
  Absolute Spatial Location
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
O. Kayhan
J. C. V. Gemert
209
232
0
16 Mar 2020
Do CNNs Encode Data Augmentations?
Do CNNs Encode Data Augmentations?
Eddie Q. Yan
Yanping Huang
OOD
11
5
0
29 Feb 2020
Deep High-Resolution Representation Learning for Visual Recognition
Deep High-Resolution Representation Learning for Visual Recognition
Jingdong Wang
Ke Sun
Tianheng Cheng
Borui Jiang
Chaorui Deng
...
Yadong Mu
Mingkui Tan
Xinggang Wang
Wenyu Liu
Bin Xiao
192
3,527
0
20 Aug 2019
Temporal Transformer Networks: Joint Learning of Invariant and
  Discriminative Time Warping
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping
Suhas Lohit
Qiao Wang
P. Turaga
ViT
9
56
0
13 Jun 2019
Why do deep convolutional networks generalize so poorly to small image
  transformations?
Why do deep convolutional networks generalize so poorly to small image transformations?
Aharon Azulay
Yair Weiss
24
557
0
30 May 2018
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
266
7,634
0
03 Jul 2012
1