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

武器

Coding Prior-Driven JPEG Image Artifact RemovalIn addition, we introduce the Degradation-Aware Dynamic Adjustment Block(DADA Block), which has better nonlinear expression capabilities and can dynamically adjusts the model based on estimated quality factors. Through this improvement we further enhancing its performance in handling JPEG images wit

運(yùn)動吧

Where to?Forget: A New Attention Stability Metric for?Continual Learning Evaluationmodels producing consistent changes in terms of RoI and classification accuracy. Experiments show that our evaluation metric offers new insight for analyzing the forgetting characteristics of different continual learning algorithms.

SEEK

Integrate

Modeling and?Analysis of?Rumor Propagation Dynamics in?Social Mediaechanism, to capture the individual behaviors. The empirical analysis reveals the dynamic behavior and complexity of rumor propagation. The V-SEIR model is evaluated in different network topologies and the impact of each metric parameter is verified. By comparing the V-SEIR model with the classic pr

ADORE

Bridging Recommendations Across Domains: An Overview of?Cross-Domain Recommendationesearch directions. In an age where demand for more accurate and personalized recommendations continues to surge in our data-driven world, cross-domain recommendation systems are poised to play a pivotal role in shaping the future of information and content consumption.

glisten

Sequence Modeling Based Data Augmentation for?Micro-expression Recognitionof 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

破裂

Dual Transformer with Gated-Attention Fusion for News Disaster Image Captioning DNICC19k dataset show that our model has achieved state-of-the-art performance. It is capable of extracting refined visual information and generating more accurate and specific descriptions of disaster news images without relying on additional prior knowledge.

Condense

Constructing Personal Knowledge Graph from?Conversation via?Deep Reinforcement Learningthe 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

Adulate

Exploring the Efficacy of Interactive Digital Humans in Cultural Communicationction 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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