CNN Feature-Based Image Copy Detection with Contextual Hash Embedding
As one of the important techniques for protecting the copyrights of digital images, content-based image copy detection has attracted a lot of attention in the past few decades. The traditional content-based copy detection methods usually extract local hand-crafted features and then quantize these fe...
Main Authors: | Zhili Zhou, Meimin Wang, Yi Cao, Yuecheng Su |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-07-01
|
Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/8/7/1172 |
Similar Items
-
Video Copy Detection Using Spatio-Temporal CNN Features
by: Zhili Zhou, et al.
Published: (2019-01-01) -
Comparing bags of features, conventional convolutional neural network and alexnet for fruit recognition
by: Hamid, N.N.A.A, et al.
Published: (2019) -
An Encrypted Speech Retrieval Method Based on Deep Perceptual Hashing and CNN-BiLSTM
by: Qiuyu Zhang, et al.
Published: (2020-01-01) -
Refining deep convolutional features for improving fine-grained image recognition
by: Weixia Zhang, et al.
Published: (2017-04-01) -
Evaluation of basic convolutional neural network and bag of features for leaf recognition
by: Ibrahim, Z., et al.
Published: (2019)