Lung cancer stands as a formidable and prevalent threat, necessitating urgent attention to early diagnosis and precise treatment to mitigate its high fatality rates. In this context, the utilization of computed tomogr...
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Current diagnostic procedures, such as imaging tests and biopsies, are time intensive and prone to human error. As a result, we employed deep learning to uncover patterns and identify lung cancer from histology pictur...
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The lack of communication options for Deaf and hearing people, some may say creates a significant social disadvantage in accessing the often-bare essential services. In contrast to acoustically communicated sound patt...
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InsightNav redefines desktop interaction by harnessing cutting-edge computer vision and AI technologies to deliver a transformative user experience. Beyond its intuitive gesture-based navigation, InsightNav pioneers t...
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Glass, though ubiquitous, is difficult to recognize in an image due to its transparency. Fine-grained low-level features indicating the presence of glass, such as refraction and reflection, are weak and subtle. This c...
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Empathic dialogue plays an indispensable role in interpersonal communication. Previous methods were mainly based on carefully designed small-scale language models. With the emergence of ChatGPT, the application of lar...
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The scarcity of bilingual parallel corpus imposes limitations on exploiting the state-of-the-art supervised translation *** of the research directions is employing relations among multi-modal data to enhance ***,the r...
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The scarcity of bilingual parallel corpus imposes limitations on exploiting the state-of-the-art supervised translation *** of the research directions is employing relations among multi-modal data to enhance ***,the reliance on manually annotated multi-modal datasets results in a high cost of data *** this paper,the topic semantics of images is proposed to alleviate the above ***,topic-related images can be auto-matically collected from the Internet by search ***,topic semantics is sufficient to encode the relations be-tween multi-modal data such as texts and ***,we propose a visual topic semantic enhanced translation(VTSE)model that utilizes topic-related images to construct a cross-lingual and cross-modal semantic space,allowing the VTSE model to simultaneously integrate the syntactic structure and semantic *** the above process,topic similar texts and images are wrapped into groups so that the model can extract more robust topic semantics from a set of similar images and then further optimize the feature *** results show that our model outperforms competitive base-lines by a large margin on the Multi30k and the Ambiguous COCO *** model can use external images to bring gains to translation,improving data efficiency.
Knowledge Graph Completion (KGC) aims to predict the missing information in the (head entity)-[relation]-(tail entity) triplet. Deep Neural Networks have achieved significant progress in the relation prediction task. ...
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Biodiversity is crucial for maintaining ecosystem stability, yet global biodiversity is currently in sharp decline, necessitating urgent protective measures. Wildlife monitoring and conservation, which determine biodi...
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The hand sign recognition has one of the most important learning domains and applications in the fields of computer vision and artificial intelligence. More specifically, one type of such communication is Sign Languag...
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