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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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- Crossmodal effects of Guqin and piano music on selective attention: An event-related potential study10
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- Learning multi-level representations for image emotion recognition in the deep convolutional network7
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- Decoupled Knowledge Embedded Graph Convolutional Network for Skeleton-Based Human Action Recognition5
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- A Multiple Objects Tracking Method Based on a Combination of Camshift and Object Trajectory Tracking4
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- Hybrid Coefficient Fusion in Multi-resolution Singular Value Decomposition Domain for Medical Images2
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- Gradual Sampling and Mutual Information Maximisation for Markerless Motion Capture2
Noticing the limitation of silhouettes in resolving gesture ambiguity, this work incorporates appearance information in an illumination invariant way by maximising Mutual Information between an appearance model and the observation, which strengthens the effectiveness of the better-behaved observation likelihood.
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- Image Emotion Analysis Based on the Distance Relation of Emotion Categories via Deep Metric Learning1
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- An Improved Ejection Chain Method and Its Hybrid Versions for Solving the Traveling Salesman Problem1
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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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