Alzheimer's disease (AD) has substantial obstacles to early detection, which frequently leads to therapy delays. In this article a unique method that uses structural MRI data and multi-Relation Graph Convolutional...
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Our research project aims to introduce an artificial intelligence (AI) conversational model that can be used to efficiently communicate with multiple PDF documents. Our solution uses natural language processing algori...
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The explosion of unverified information on social media platforms has made it more important than ever to identify and anticipate false news, which poses serious hazards to democratic processes and society as a whole....
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Human Activity Recognition (HAR) is crucial for the development of intelligent assistive technologies in Ambient Assisted Living (AAL) environments. This paper proposes an innovative method for multi-View Human Activi...
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This paper presents the results of the international Workshop on Human-Centered Software engineering, which was part of the 19th internationalconference promoted by the IFIP Technical Committee 13 on Human-computer I...
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ISBN:
(纸本)9783031616877;9783031616884
This paper presents the results of the international Workshop on Human-Centered Software engineering, which was part of the 19th internationalconference promoted by the IFIP Technical Committee 13 on Human-computer Interaction (Interact 2023). The leading topic of this edition of the workshop was "Rethinking the Interplay of Human-computer Interaction and Software engineering in the Age of Digital Transformation". The workshop was characterized by an innovative format designed to bolster research efforts across various stages. Ten papers were presented by authors and discussed in the workshop. In terms of topics, there were three key sessions focusing on digitizing manufacturing processes, understanding users, and digitization for smart life Seven of these papers were extended in these proceedings.
In practical applications, implementing reinforcement learning in multi-Agent environments is very important. Most of the existing multi-Agent reinforcement learning algorithms lack communication capabilities, forcing...
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In the current medical field, survival prediction for breast cancer patients has increasingly relied on multimodal data, driven by rapid advancements in medical imaging technology and genomics. These developments prov...
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Swin Transformer has become a paradigm for high-level vision tasks. However, its application in image reconstruction is hampered by the fixed window size and high-resolution feature maps, which restrict the extent of ...
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In the digital age, the spread of fake news has become ubiquitous: it weakens public speech and weakens public trust. In this paper we propose a novel method of detecting fake news using a deep learning framework. To ...
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Traditional relation extraction methods are usually based on single text data, and other modality information such as image and video can improve the effect of text relation extraction. Aiming at the problem of hetero...
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