Abstract
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JinXian Zhang, Zuowen Jiang, Yuhang Zhou, Zhouyan He, Chuan Zhang, Ting Luo
Abstract
Authors
Institutions
Provenance
crossref
Confidence 100%
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Image steganalysis using active learning and hyperparameter optimization
10.1038/s41598-025-92082-w · 2025
A novel image gravity transform based on least significant bit in image steganography
10.1016/j.matcom.2025.03.010 · 2025
A novel and efficient digital image steganography technique using least significant bit substitution
10.1038/s41598-024-83147-3 · 2025
High-security image steganography integrating multi-scale feature fusion with residual attention mechanism
10.1016/j.neucom.2025.129838 · 2025
A review on spatial domain technique based on image steganography
2017
GAN-based spatial image steganography with cross feedback mechanism
10.1016/j.sigpro.2021.108341 · 2022
Recent advances of image steganography with generative adversarial networks
10.1109/access.2020.2983175 · 2020
Invisible steganography via generative adversarial networks
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HSDetect-Net: A fuzzy-based deep learning steganalysis framework to detect possible hidden data in digital images
openalex
Confidence 95%
datacite
Confidence 0%
2025
Towards robust image steganography
10.1109/tcsvt.2018.2881118 · 2018
Robust steganography for high quality images
10.1109/tcsvt.2023.3250750 · 2023
High-accuracy image steganography with invertible neural network and generative adversarial network
10.1016/j.sigpro.2025.109988 · 2025
10.1109/cvpr52729.2023.02165
10.1109/cvpr52729.2023.02165
A survey on Deep-Learning-based image steganography
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Hiding images in plain sight: Deep steganography
2017
Unresolved referenced work
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Deep adaptive hiding network for image hiding using attentive frequency extraction and gradual depth extraction
10.1007/s00521-023-08274-w · 2023
Joint adjustment image steganography networks
10.1016/j.image.2023.117022 · 2023
Channel attention image steganography with generative adversarial networks
10.1109/tnse.2021.3139671 · 2021
AFcIHNet: Attention feature-constrained network for single image information hiding
10.1016/j.engappai.2023.107105 · 2023
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DeepMIH: Deep invertible network for multiple image hiding
10.1109/tpami.2022.3141725 · 2022
iSCMIS: Spatial-channel attention based deep invertible network for multi-image steganography
10.1109/tmm.2023.3307970 · 2023
NiNet: A new invertible neural network architecture more suitable for deep image hiding
10.1016/j.ipm.2025.104275 · 2025
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Neural networks-based data hiding in digital images: Overview
10.1016/j.neucom.2024.127499 · 2024
Steganalysis feature selection with multidimensional evaluation and dynamic threshold allocation
10.1109/tcsvt.2023.3295364 · 2023
EIS-OBEA: Enhanced image steganalysis via opposition-based evolutionary algorithm
10.1109/tifs.2025.3549692 · 2025
Discrete cosine transform
10.1109/t-c.1974.223784 · 2006
Unresolved referenced work
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10.1109/cvprw.2017.150
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2014
Universal deep network for steganalysis of color image based on channel representation
10.1109/tifs.2022.3196265 · doi-reference
Depth-wise separable convolutions and multi-level pooling for an efficient spatial CNN-based steganalysis
10.1109/tifs.2019.2936913 · doi-reference
Deep residual network for steganalysis of digital images
10.1109/tifs.2018.2871749 · doi-reference
Imagenet large scale visual recognition challenge
10.1007/s11263-015-0816-y · doi-reference
10.1109/cvprw.2017.150
10.1109/cvprw.2017.150 · doi-reference
Design of an image edge detection filter using the Sobel operator
10.1109/4.996 · doi-reference
Discrete cosine transform
10.1109/t-c.1974.223784 · doi-reference
EIS-OBEA: Enhanced image steganalysis via opposition-based evolutionary algorithm
10.1109/tifs.2025.3549692 · doi-reference
Steganalysis feature selection with multidimensional evaluation and dynamic threshold allocation
10.1109/tcsvt.2023.3295364 · doi-reference
Neural networks-based data hiding in digital images: Overview
10.1016/j.neucom.2024.127499 · doi-reference
10.1609/aaai.v36i3.20267
10.1609/aaai.v36i3.20267 · doi-reference
NiNet: A new invertible neural network architecture more suitable for deep image hiding
10.1016/j.ipm.2025.104275 · doi-reference
iSCMIS: Spatial-channel attention based deep invertible network for multi-image steganography
10.1109/tmm.2023.3307970 · doi-reference
DeepMIH: Deep invertible network for multiple image hiding
10.1109/tpami.2022.3141725 · doi-reference
10.1109/iccv48922.2021.00469
10.1109/iccv48922.2021.00469 · doi-reference
10.1609/aaai.v38i3.28051
10.1609/aaai.v38i3.28051 · doi-reference
AFcIHNet: Attention feature-constrained network for single image information hiding
10.1016/j.engappai.2023.107105 · doi-reference
Channel attention image steganography with generative adversarial networks
10.1109/tnse.2021.3139671 · doi-reference
Joint adjustment image steganography networks
10.1016/j.image.2023.117022 · doi-reference
Deep adaptive hiding network for image hiding using attentive frequency extraction and gradual depth extraction
10.1007/s00521-023-08274-w · doi-reference
A survey on Deep-Learning-based image steganography
10.1016/j.eswa.2024.124390 · doi-reference
10.1109/cvpr52729.2023.02165
10.1109/cvpr52729.2023.02165 · doi-reference
High-accuracy image steganography with invertible neural network and generative adversarial network
10.1016/j.sigpro.2025.109988 · doi-reference
Robust steganography for high quality images
10.1109/tcsvt.2023.3250750 · doi-reference
Towards robust image steganography
10.1109/tcsvt.2018.2881118 · doi-reference
Invisible steganography via generative adversarial networks
10.1007/s11042-018-6951-z · doi-reference
Recent advances of image steganography with generative adversarial networks
10.1109/access.2020.2983175 · doi-reference
GAN-based spatial image steganography with cross feedback mechanism
10.1016/j.sigpro.2021.108341 · doi-reference
High-security image steganography integrating multi-scale feature fusion with residual attention mechanism
10.1016/j.neucom.2025.129838 · doi-reference
A novel and efficient digital image steganography technique using least significant bit substitution
10.1038/s41598-024-83147-3 · doi-reference
A novel image gravity transform based on least significant bit in image steganography
10.1016/j.matcom.2025.03.010 · doi-reference
Image steganalysis using active learning and hyperparameter optimization
10.1038/s41598-025-92082-w · doi-reference