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- Temporal relative transformer encoding cooperating with channel attention for EEG emotion analysis65
A temporal relative (TR) encoding mechanism is proposed to encode the temporal EEG signals for constructing the temporality self-attention in the transformer and experimental results demonstrate that the model outperforms the advanced methods for all classification tasks.
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- Generate adversarial examples by adaptive moment iterative fast gradient sign method37
This work proposes the adaptive moment iterative fast gradient sign method (Adam-FGSM), a new iterative white-box attack that could adopt rugged input loss space to generate adversarial examples with a higher attack success rate and acceptable transferability in fewer iterations.
- Image Segmentation Based on Improved Unet36
Comparing multiple sets of experiments, compared with general network structures such as Unet and AttenUnet, it shows that the network architecture proposed in the Dissertation improves the accuracy and efficiency of liver image segmentations.
- Adaptive low light visual enhancement and high-significant target detection for infrared and visible image fusion35
Qualitative and quantitative experimental results demonstrate that the proposed method is superior to 9 state-of-the-art image fusion methods as more valuable texture details and significant infrared targets are preserved.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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