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A Two-Phase Scheme by Integration of Deep and Corner Feature for Balanced Copy-Move Forgery Localization
In the era of Industry 4.0, the widespread application of digitization, automation, and Internet technology in industrial production …
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Black-Box Reversible Adversarial Examples with Invertible Neural Network
Reversible Adversarial Example (RAE) has been widely researched for its ability to ensure authorized access while preventing …
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Encryption-Then-Embedding-Based Hybrid Data Hiding Scheme for Medical Images
The smart healthcare system plays a vital role in modern healthcare, facilitating the exchange of Electronic Patient Records (EPR), …
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F3Net: Feature Filtering Fusing Network for Change Detection of Remote Sensing Images
Change detection of remote sensing images is an essential method for observing changes on the Earth's surface. Deep learning can …
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HEDN: Multi-Oriented Hierarchical Extraction and Dual-Frequency Decoupling Network for 3D Medical Image Segmentation
Previous 3D encoder-decoder segmentation architectures struggled with fine-grained feature decomposition, resulting in unclear feature …
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Image Manipulation Localization Using Dual-Shallow Feature Pyramid Fusion and Boundary Contextual Incoherence Enhancement
This paper proposes a novel end-to-end network for Image Manipulation Localization (IML) comprising three modules: feature fusion, …
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Large kernel convolution application for land cover change detection of remote sensing images
In land cover change detection tasks, extracting universal features of changing targets is crucial for achieving precise detection …
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LungNeXt: A novel lightweight network utilizing enhanced mel-spectrogram for lung sound classification
Lung auscultation is essential for early lung condition detection. Categorizing adventitious lung sounds requires expert …
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MMQW: Multi-Modal Quantum Watermarking Scheme
To address the problem that existing quantum image watermarking schemes have only a single watermarking mode with weak robustness, in …
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Multi-Granularity Hypergraph-Guided Transformer Learning Framework for Visual Classification
Fine-grained single-label classification tasks aim to distinguish highly similar categories but often overlook inter-category …
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