AAU-Net: attention-based asymmetric U-Net for subject-sensitive hashing of remote sensing images

K Ding, S Chen, Y Wang, Y Liu, Y Zeng, J Tian - Remote Sensing, 2021 - mdpi.com
The prerequisite for the use of remote sensing images is that their security must be
guaranteed. As a special subset of perceptual hashing, subject-sensitive hashing …

Semi-U-Net: A Lightweight Deep Neural Network for Subject-Sensitive Hashing of HRRS Images

K Ding, S Su, N Xu, T Jiang - IEEE Access, 2021 - ieeexplore.ieee.org
As a special case of perceptual hashing algorithm, subject-sensitive hashing can realize
“subject-biased” integrity authentication of high resolution remote sensing (HRRS) images …

SDTU-Net: Stepwise-Drop and Transformer based U-net for Subject-Sensitive Hashing of HRRS Images

K Ding, S Chen, Y Zeng, Y Liu, B Xu… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
As a new integrity authentication technology, subject-sensitive hashing has the ability to
achieve subject-sensitive authentication for high-resolution remote sensing (HRRS) images …

AGIM-net based subject-sensitive hashing algorithm for integrity authentication of HRRS images

K Ding, Y Zeng, Y Wang, D Lv, X Yan - Geocarto International, 2023 - Taylor & Francis
The premise of effective use of high-resolution remote sensing (HRRS) images is that the
data integrity and authenticity of HRRS images must be guaranteed. This paper proposes a …

WeGAN: Deep image hashing with weighted generative adversarial networks

Y Wang, L Zhang, F Nie, X Li, Z Chen… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Image hashing has been widely used in image retrieval tasks. Many existing methods
generate hashing codes based on image feature representations. They rarely consider the …

Robust mutual learning hashing

L Wu, Y Fang, H Ling, J Chen… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
With the advances in deep learning, deep hashing methods have achieved promising
results in recent years. However, tackling the distribution gap between train data and test …

Multi-granularity feature learning network for deep hashing

H Feng, N Wang, J Tang, J Chen, F Chen - Neurocomputing, 2021 - Elsevier
With the ever-increasing growth of massive high-dimensional data, deep learning to hash
technology has been widely used for approximate nearest neighbor search on large-scale …

Pairwise teacher-student network for semi-supervised hashing

S Zhang, J Li, B Zhang - … of the IEEE/CVF Conference on …, 2019 - openaccess.thecvf.com
Hashing method maps similar high-dimensional data to binary hashcodes with smaller
hamming distance, and it has received broad attention due to its low storage cost and fast …

Deep supervised hashing based on stable distribution

L Wu, H Ling, P Li, J Chen, Y Fang, F Zhou - IEEE Access, 2019 - ieeexplore.ieee.org
Recently, the convolutional neural network (CNN)-based hashing method has achieved its
promising performance for image retrieval. However, tackling the discrepancy between …

Mixture of Experts Residual Learning for Hamming Hashing

J Xu, Q Xie, J Li, Y Ma, Y Liu - Neural Processing Letters, 2023 - Springer
Image retrieval has drawn growing attention due to the rapid emergence of images on the
Internet. Due to the high storage and computation efficiency, hashing methods are widely …