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. 1601.02919
  4. Cited By
Using Filter Banks in Convolutional Neural Networks for Texture
  Classification

Using Filter Banks in Convolutional Neural Networks for Texture Classification

12 January 2016
Vincent Andrearczyk
P. Whelan
    3DV
ArXivPDFHTML

Papers citing "Using Filter Banks in Convolutional Neural Networks for Texture Classification"

19 / 19 papers shown
Title
Empirical curvelet based Fully Convolutional Network for supervised
  texture image segmentation
Empirical curvelet based Fully Convolutional Network for supervised texture image segmentation
Yuan Huang
Fugen Zhou
Jerome Gilles
32
22
0
28 Oct 2024
Structural and Statistical Texture Knowledge Distillation for Semantic Segmentation
Structural and Statistical Texture Knowledge Distillation for Semantic Segmentation
Deyi Ji
Haoran Wang
Mingyuan Tao
Jianqiang Huang
Xiansheng Hua
Hongtao Lu
35
61
0
06 May 2023
TFN: An Interpretable Neural Network with Time-Frequency Transform
  Embedded for Intelligent Fault Diagnosis
TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis
Qian Chen
Xingjian Dong
Guowei Tu
Dong Wang
Baoxuan Zhao
Zhike Peng
AI4CE
16
66
0
05 Sep 2022
Texture Extraction Methods Based Ensembling Framework for Improved
  Classification
Texture Extraction Methods Based Ensembling Framework for Improved Classification
V. Pandey
Trapti Kalra
Mayank Gubba
Mohammed Faisal
28
0
0
08 Jun 2022
Group-invariant max filtering
Group-invariant max filtering
Jameson Cahill
Joseph W. Iverson
D. Mixon
Dan Packer
36
22
0
27 May 2022
Multiscale Analysis for Improving Texture Classification
Multiscale Analysis for Improving Texture Classification
S. Ataky
D. Saqui
Jonathan de Matos
A. Britto
Alessandro Lameiras Koerich
19
7
0
21 Apr 2022
Magnification Prior: A Self-Supervised Method for Learning
  Representations on Breast Cancer Histopathological Images
Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images
Prakash Chandra Chhipa
Richa Upadhyay
G. Pihlgren
Rajkumar Saini
Seiichi Uchida
Marcus Liwicki
SSL
MedIm
33
19
0
15 Mar 2022
VisGraphNet: a complex network interpretation of convolutional neural
  features
VisGraphNet: a complex network interpretation of convolutional neural features
J. Florindo
Young-Sup Lee
Kyungkoo Jun
Gwanggil Jeon
M. Albertini
FAtt
GNN
23
14
0
27 Aug 2021
Deep Learning Approaches to Classification of Production Technology for
  19th Century Books
Deep Learning Approaches to Classification of Production Technology for 19th Century Books
Chanjong Im
J. Ghauri
John Rothman
Thomas Mandl
16
1
0
17 Sep 2020
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale
  Multi-phase CT Data via Deep Dynamic Texture Learning
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning
Yuankai Huo
Jinzheng Cai
Chi-Tung Cheng
Ashwin Raju
K. Yan
Bennett A. Landman
Jing Xiao
Le Lu
Chien-Hung Liao
Adam P. Harrison
MedIm
24
11
0
28 Jun 2020
Local Rotation Invariance in 3D CNNs
Local Rotation Invariance in 3D CNNs
Vincent Andrearczyk
Julien Fageot
Valentin Oreiller
X. Montet
Adrien Depeursinge
42
23
0
19 Mar 2020
Rotational 3D Texture Classification Using Group Equivariant CNNs
Rotational 3D Texture Classification Using Group Equivariant CNNs
Vincent Andrearczyk
Adrien Depeursinge
21
12
0
16 Oct 2018
Wavelet Convolutional Neural Networks
Wavelet Convolutional Neural Networks
S. Fujieda
Kohei Takayama
T. Hachisuka
11
125
0
20 May 2018
Texture Segmentation Based Video Compression Using Convolutional Neural
  Networks
Texture Segmentation Based Video Compression Using Convolutional Neural Networks
Chichen Fu
Di Chen
Edward J. Delp
Zoe Liu
F. Zhu
16
8
0
08 Feb 2018
From BoW to CNN: Two Decades of Texture Representation for Texture
  Classification
From BoW to CNN: Two Decades of Texture Representation for Texture Classification
Li Liu
Jie Chen
Paul Fieguth
Guoying Zhao
Rama Chellappa
M. Pietikäinen
3DV
39
332
0
31 Jan 2018
A concatenating framework of shortcut convolutional neural networks
A concatenating framework of shortcut convolutional neural networks
Yujian Li
Ting Zhang
Zhaoying Liu
Haihe Hu
20
10
0
03 Oct 2017
A Hybrid Deep Learning Approach for Texture Analysis
A Hybrid Deep Learning Approach for Texture Analysis
Hussein Adly
Mohamed Moustafa
4
5
0
24 Mar 2017
Learning Multi-level Deep Representations for Image Emotion
  Classification
Learning Multi-level Deep Representations for Image Emotion Classification
T. Rao
Min Xu
Dong Xu
25
140
0
22 Nov 2016
Deep convolutional filter banks for texture recognition and segmentation
Deep convolutional filter banks for texture recognition and segmentation
Mircea Cimpoi
Subhransu Maji
Andrea Vedaldi
3DV
34
53
0
25 Nov 2014
1