This paper presents an Arabic Alphabet Sign Language recognition approach, using deep learning methods in conjunction with transfer learning and transformer-based models. We study the performance of the different vari...
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ISBN:
(数字)9798350367560
ISBN:
(纸本)9798350367577
This paper presents an Arabic Alphabet Sign Language recognition approach, using deep learning methods in conjunction with transfer learning and transformer-based models. We study the performance of the different variants on two publicly available datasets, namely ArSL2018 and AASL. This task will make full use of state-of-the-art CNN architectures like ResNet50, MobileNetV2, and EfficientNetB7, and the latest transformer models such as Google ViT and Microsoft Swin Transformer. These pre-trained models have been fine-tuned on the above datasets in an attempt to capture some unique features of Arabic sign language motions. Experimental results present evidence that the suggested methodology can receive a high recognition accuracy, by up to 99.6% and 99.43% on ArSL2018 and AASL, respectively. That is far beyond the previously reported state-of-the-art approaches. This performance opens up even more avenues for communication that may be more accessible to Arabic-speaking deaf and hard-of-hearing, and thus encourages an inclusive society.
Enterprises are often concerned about disasters, particularly accidents involving personnel. Therefore, there is ongoing research dedicated to safeguarding the safety of employees within enterprises. In recent years, ...
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Mobile Edge Caching (MEC) can potentially alleviate Internet transmission congestion by delivering content at the network edge. However, current MEC solutions suffer from low resource utilization efficiency and often ...
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The research examines how Green Artificial Intelligence (AI) impacts agricultural and biological domains by analysing relevant literature using bibliometrics. Green AI, which prioritizes sustainability and environment...
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ISBN:
(数字)9798331528553
ISBN:
(纸本)9798331528560
The research examines how Green Artificial Intelligence (AI) impacts agricultural and biological domains by analysing relevant literature using bibliometrics. Green AI, which prioritizes sustainability and environmental awareness, is proving to be an asset in tackling the issues in agriculture and biology. The investigation examines a wide range of academic publications, patents, and research papers to identify significant trends, research topics, and the influence of Green AI on agricultural and biological fields. The research shows an increasing amount of literature investigating the combination of AI technology with green principles to improve resource management, boost agricultural output, and reduce environmental effects. This study uses analysis of citation networks, co-authorship patterns, and theme grouping to get insights into the present status and future trends of research in the fields of Green AI, agriculture, and biology. The data was extracted from the database maintained by Scopus using the PRISM Model. 11,142 article data points were used for the analysis of Green AI. This bibliometric study enhances comprehension of the changing environment of Green AI applications in agricultural and biological areas, providing vital recommendations for academics, policymakers, and practitioners working towards sustainable development objectives.
Thousands of individuals succumb annually to leukemia alone. As artificial intelligence-driven technologies continue to evolve and advance, the question of their applicability and reliability remains unresolved. This ...
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CBDC–as-a-problem looks like a mania of interest from central banks and financial institutions all over the world. It may describe CBDC technology and CBDC technology development, the positive aspects of CBDC and its...
CBDC–as-a-problem looks like a mania of interest from central banks and financial institutions all over the world. It may describe CBDC technology and CBDC technology development, the positive aspects of CBDC and its future perspectives as follows: The CBDC is linked to the existing banking systems in the past which was based on the past findings of the blockchain, DLT, etc., that possessed the qualities the previous ones did not have – security, trust, and transparency. Innovation, design and CBDC safety that falls below this paper are discussed in this section below. The paper proceeds to show several paths that central banks are taking to CBDC development given the regulation and changing dynamic of the financial world. However, the studies do not end there; information on the potential of CBDC for financial stability, monetary policy formulation trajectories, transaction privacy, and the role of banks is included. Given that in field of finance the CBDCs are becoming more and more important, this research paper shall ensure to provide consistent background to policymakers, financial institutions and society at large on CBDC and its structural implications. This guarantees that everyone is in the know so it will be possible for them to come up with compliant plans and decisions informed by the knowledge in this changing landscape that simply does not stop evolving.
Feature selection is a cornerstone in advancing the accuracy and efficiency of predictive models, particularly in nuanced domains like socio-economic analysis. This study explores nine distinct feature selection metho...
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Recently, banks are constantly facing the problem of customers churning. Customer churn not only leads to a decline in bank funds and profits but also reduces its credit capacity and affects the bank’s operational ma...
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作者：
Lu, LinZou, Qingzhi
Key Laboratory of Computing Power Network and Information Se-curity Ministry of Education Shandong Computer Science Center Jinan China
Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Provincial Key Laboratory of Computer Networks
Shandong Fundamental Research Center for Computer Science Jinan China
Due to the exceptional performance of Transform-ers in 2D medical image segmentation, recent work has also introduced them into 3D medical segmentation tasks. For instance, Swin UNETR and other hierarchical Transforme...
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In the current digital landscape, safeguarding digital content from unauthorized sharing is of paramount importance. This study concerns three key issues: the prevalent unauthorized sharing of content, user dissatisfa...
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ISBN:
(数字)9798350353839
ISBN:
(纸本)9798350353846
In the current digital landscape, safeguarding digital content from unauthorized sharing is of paramount importance. This study concerns three key issues: the prevalent unauthorized sharing of content, user dissatisfaction with existing security measures, and the lack of alignment between expert opinions and user perceptions. This research addresses three critical problem statements. Firstly, it seeks to identify the current security features utilized to prevent the unauthorized distribution of digital content. Secondly, it aims to assess user perceptions of these features through a meticulously constructed survey; and lastly, the study endeavors to compare findings from a thorough literature review with user perceptions. Methodologically, this research encompasses an exhaustive literature review and a user perception survey to gain insights into effective security measures and recommendations for enhancement. The expected outcomes include a more profound understanding of the effectiveness of current security measures and suggestions for enhancing digital content protection. Through this study, it has been emphasized the significance of digital content security and put forward collaborative avenues for improvement.
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