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. 1705.01450
  4. Cited By
Gabor Convolutional Networks

Gabor Convolutional Networks

3 May 2017
Shangzhen Luan
Baochang Zhang
Chen Chen
Xianbin Cao
J. Han
Jianzhuang Liu
    BDL
ArXivPDFHTML

Papers citing "Gabor Convolutional Networks"

20 / 70 papers shown
Title
Searching Central Difference Convolutional Networks for Face
  Anti-Spoofing
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
Zitong Yu
Chenxu Zhao
Zezheng Wang
Yunxiao Qin
Z. Su
Xiaobai Li
Feng Zhou
Guoying Zhao
CVBM
67
410
0
09 Mar 2020
Scale-Invariant Multi-Oriented Text Detection in Wild Scene Images
Scale-Invariant Multi-Oriented Text Detection in Wild Scene Images
Kinjal Dasgupta
Sudip Das
Ujjwal Bhattacharya
6
8
0
15 Feb 2020
Harmonic Convolutional Networks based on Discrete Cosine Transform
Harmonic Convolutional Networks based on Discrete Cosine Transform
Matej Ulicny
V. Krylov
Rozenn Dahyot
27
34
0
18 Jan 2020
Convolutional Neural Networks: A Binocular Vision Perspective
Convolutional Neural Networks: A Binocular Vision Perspective
Yigit Oktar
Diclehan Karakaya
Oguzhan Ulucan
Mehmet Türkan
14
2
0
21 Dec 2019
Gabor Layers Enhance Network Robustness
Gabor Layers Enhance Network Robustness
Juan C. Pérez
Motasem Alfarra
Guillaume Jeanneret
Adel Bibi
Ali K. Thabet
Guohao Li
Pablo Arbelaez
AAML
22
17
0
11 Dec 2019
Naive Gabor Networks for Hyperspectral Image Classification
Naive Gabor Networks for Hyperspectral Image Classification
Chenying Liu
Jun Li
Lin He
Antonio J. Plaza
Shutao Li
Bo Li
37
45
0
09 Dec 2019
Object Detection in Optical Remote Sensing Images: A Survey and A New
  Benchmark
Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark
Ke Li
G. Wan
Gong Cheng
L. Meng
Junwei Han
16
1,414
0
31 Aug 2019
Towards Learning Affine-Invariant Representations via Data-Efficient
  CNNs
Towards Learning Affine-Invariant Representations via Data-Efficient CNNs
Xenju Xu
Guanghui Wang
Alan Sullivan
Ziming Zhang
30
23
0
31 Aug 2019
On the Realization and Analysis of Circular Harmonic Transforms for
  Feature Detection
On the Realization and Analysis of Circular Harmonic Transforms for Feature Detection
H. L. Kennedy
14
2
0
29 Jul 2019
Filter Bank Regularization of Convolutional Neural Networks
Filter Bank Regularization of Convolutional Neural Networks
Seyed Mehdi Ayyoubzadeh
Xiaolin Wu
9
0
0
25 Jul 2019
Learning Complex Basis Functions for Invariant Representations of Audio
Learning Complex Basis Functions for Invariant Representations of Audio
Stefan Lattner
M. Dörfler
A. Arzt
14
13
0
13 Jul 2019
Multifaceted Analysis of Fine-Tuning in Deep Model for Visual
  Recognition
Multifaceted Analysis of Fine-Tuning in Deep Model for Visual Recognition
Xiangyang Li
Luis Herranz
Shuqiang Jiang
15
2
0
11 Jul 2019
Provably scale-covariant continuous hierarchical networks based on
  scale-normalized differential expressions coupled in cascade
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade
T. Lindeberg
27
19
0
29 May 2019
Inductive Guided Filter: Real-time Deep Image Matting with Weakly
  Annotated Masks on Mobile Devices
Inductive Guided Filter: Real-time Deep Image Matting with Weakly Annotated Masks on Mobile Devices
Yaoyi Li
Jianfu Zhang
Weijie Zhao
Hongtao Lu
26
5
0
16 May 2019
Harmonic Networks with Limited Training Samples
Harmonic Networks with Limited Training Samples
Matej Ulicny
V. Krylov
Rozenn Dahyot
14
17
0
30 Apr 2019
GaborNet: Gabor filters with learnable parameters in deep convolutional
  neural networks
GaborNet: Gabor filters with learnable parameters in deep convolutional neural networks
Andrey Sergeevich Alekseev
Anatoly Bobe
13
67
0
30 Apr 2019
Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural
  Networks
Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks
Domen Tabernik
Matej Kristan
A. Leonardis
16
22
0
20 Feb 2019
What Do We Understand About Convolutional Networks?
What Do We Understand About Convolutional Networks?
Isma Hadji
Richard P. Wildes
FAtt
16
98
0
23 Mar 2018
Spatially-Adaptive Filter Units for Deep Neural Networks
Spatially-Adaptive Filter Units for Deep Neural Networks
Domen Tabernik
Matej Kristan
A. Leonardis
18
11
0
30 Nov 2017
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
7,638
0
03 Jul 2012
Previous
12