Sign Language Recognition (SLR) has garnered significant attention from researchers in recent years, particularly the intricate domain of Continuous Sign Language Recognition (CSLR), which presents heightened complexi...
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Rule-induction models have demonstrated great power in the inductive setting of knowledge graph completion. In this setting, the models are tested on a knowledge graph entirely composed of unseen entities. These ...
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360∘ videos have become increasingly popular recently, but consume much more bandwidth than non-360∘ videos. Usually, 360∘ video streaming partitions the video surface into multiple tiles and encodes the tiles inde...
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Convolutional Neural Networks (CNNs) have become instrumental in advancing image classification, particularly in the context of garbage image classification, a critical component for efficient waste management. This p...
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Natural Language Processing (NLP) is increasingly pivotal in the natural sciences, with sentiment analysis emerging as a crucial application in the era of big data. Efficiently and accurately extracting meaningful ins...
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Depression has the potential to impact death rates, particularly when it comes to death by suicide. Inadequate diagnosis may result in a delay or unsuitable therapy, which can worsen symptoms of depression. Unaddresse...
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In computational linguistics, effectively encoding and systematizing emotional expressions in language is a significant challenge. Existing machine learning (ML) models for text analysis often only recognize primary e...
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This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain *** combining the strengths of blockchain and generati...
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This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain *** combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical *** participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security *** multi faceted exploration led to an indepth evaluation of the model’s performance and ***,the correlation between accuracy,detection rate,and error rate was *** analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance *** study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical *** blockchain to generative AI-created medical content addresses key personal information protection *** utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical *** approach not only enhances security but also enables transparent and tamperproof ***,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient *** conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient *** proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content *** research and advancements
Carbon neutrality is a global target pursued by cities worldwide to achieve a balance between carbon emissions and removals, reaching a net-zero carbon state. Mitigation measures are being implemented to reduce emissi...
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Bias detection and mitigation is an active area of research in machine learning. This work extends previous research done by the authors Van Busum and Fang (Proceedings of the 38th ACM/SIGAPP Symposium on Applied Comp...
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