As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of larg...
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As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of larg...
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As an important component of the space-air-ground integrated network, aerial base station (AeBS) systems have gained significant attention for their flexibility in mobility and cost-effective construction. Nevertheles...
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Groundbreaking applications such as ChatGPT have heightened research interest in generative artificial intelligence (GAI). Essentially, GAI excels not only in content generation but also signal processing, offering su...
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Nowadays, the deterioration of water resources leads to negative ecological impacts. To effectively inhibit the deterioration of water resources, a water quality prediction model based on enhanced transformer, sliding...
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ISBN:
(数字)9798350358513
ISBN:
(纸本)9798350358520
Nowadays, the deterioration of water resources leads to negative ecological impacts. To effectively inhibit the deterioration of water resources, a water quality prediction model based on enhanced transformer, sliding block, and channel independence (WaterTS) is proposed by comprehensively analyzing the indicators of water resources and making long-term predictions of the dissolved oxygen index. WaterTS adopts a sliding block method to extract the short-term temporal features of the water quality series and combine them with channel independence to make independent predictions of multi-featured data. Moreover, it upgrades the internal encoder structure of the transformer and improves the attention mechanism to Probsparse-attention and Auto-Correlation to speed up the prediction speed. Furthermore, Post LayerNormal is adjusted to Pre LayerNormal, which makes the training gradient more stable and enhances the accuracy of predictions. Experiments are conducted using real-world water environment data, and comparison results with state-of-the-art prediction models show that the WaterTS achieves accurate predictions on both short-term and long-term water quality data.
This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cu...
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Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output ...
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ISBN:
(数字)9798331527471
ISBN:
(纸本)9798331527488
Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model's capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods.
Temporal relation extraction (TRE) aims to grasp the evolution of events or actions, and thus shape the workflow of associated tasks, so it holds promise in helping understand task requests initiated by requesters in ...
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Timely status updating is the premise of emerging interaction-based applications in the Internet of Things (IoT). Using redundant devices to update the status of interest is a promising method to improve the timelines...
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Semantic communication is an important participant in the next generation of wireless communications. Enabled by this novel paradigm, the conventional Internet-of-Things (IoT) is evolving toward the semantic IoT (SIoT...
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