Titlebook: Digital Multimedia Communications; 20th International F Guangtao Zhai,Jun Zhou,Xiaokang Yang Conference proceedings 2024 The Editor(s) (if

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https://doi.org/10.1007/978-1-4613-1755-5of class-imbalance, we propose a balanced loss function, in which the loss of each category is weighted by a factor determined by both the actual sample size and effective sample size of this category. Experimental results on three benchmark ME databases demonstrate the superiority of our approach o

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the reinforcement learning policy network. We conduct experiments on the ConvRef dataset, consisting of 11k naturally occurring dialogues, and compare our method with state-of-the-art baselines. The results demonstrate that our approach effectively generates more accurate inference paths from user-a

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ction fostering greater public absorption of historical and cultural content, thus expanding the potential applications of digital humans. In conclusion, digital human technology is poised to offer a novel and efficient technological means for cultural communication, injecting new possibilities into

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RAUNE-Net: A Residual and Attention-Driven Underwater Image Enhancement Methodns. The experimental validation demonstrates that our method obtains promising objective performance and consistent visual results across various real-world underwater images compared to other eight UIE methods. Our example code and datasets are publicly available at ..

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Depth Map Super-Resolution via Asymmetrically Guided Feature Selection and Spatial Affine Transformahensively integrate the information from RGB modal, are then employed to reconstruct high-resolution depth maps. In other words, The asymmetry is reflected in the fact that we only explicitly update the depth features. The effectiveness of our approach is demonstrated through quantitative and qualit

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Wide Activation Fourier Channel Attention Network for Super-Resolutionourier channel attention super-resolution network (WFCASR) to enhance the residual block by incorporating the wide activation mechanism and FCA. Results in the development of. By integrating the FCA block and the wide activation mechanism into our network, the high-frequency information can be effec

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LightNet+: Boosted Light-Weighted Network for Smoke Semantic Segmentation a novel Attention-guided Coupled Feature Fusion Module (ACFFM) that introduces Self-Refinement Coefficients (SRCs) generated from cross-layer fusion to weight the original layer images. This two-stage fusion approach effectively utilizes information from different scales to alleviate the impact of

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