Simile tasks are challenging in natural language processing (NLP) because models require adequate world knowledge to produce predictions. In recent years, pre-trained language models (PLMs) have succeeded in NLP since...
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Machine learning has become important for anomaly detection in water quality prediction. Data anomalies are often caused by the difficulties of analysing large amounts of data, both technical and human, but approaches...
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Nested Event Extraction (NEE) aims to extract complex event structures where an event contains other events as its arguments recursively. Nested events involve a kind of Pivot Elements (PEs) that simultaneously act as...
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The gaming industry is getting more attraction from cloud services providing gaming applications for cooperative multiplayer gaming. Real-time services like cloud gaming are possible by performing necessary process-in...
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This study employs transfer learning using a fine-tuned pretrained EfficientNetB0 convolutional neural network (CNN) model to accurately detect the various stages of Diabetic Retinopathy. The training process involved...
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Automatic Human Action Recognition (HAR) using RGB-D (Red, Green, Blue, and Depth) videos captivated a lot of attention in the pattern classification field due to low-cost depth cameras. Feature extraction in action r...
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technology-enhanced learning has the potential to increase educational quality. In this study, we examine the integration of augmented reality (AR) technology in rural primary schools in India. We listed articles asso...
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Diabetes is a common disease that causes complications in the eyes known as Diabetic Retinopathy (DR). It aids in discovering the DR and tends to be the main cause behind people’s blindness amidst the previous decade...
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The rapid growth of smart technologies and services has intensified the challenges surrounding identity authenti-cation *** credentials are increasingly being used for verification due to their advantages over traditi...
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The rapid growth of smart technologies and services has intensified the challenges surrounding identity authenti-cation *** credentials are increasingly being used for verification due to their advantages over traditional methods,making it crucial to safeguard the privacy of people’s biometric data in various *** paper offers an in-depth exploration for privacy-preserving techniques and potential threats to biometric *** proposes a noble and thorough taxonomy survey for privacy-preserving techniques,as well as a systematic framework for categorizing the field’s existing *** review the state-of-the-art methods and address their advantages and limitations in the context of various biometric modalities,such as face,fingerprint,and eye *** survey encompasses various categories of privacy-preserving mechanisms and examines the trade-offs between security,privacy,and recognition performance,as well as the issues and future research *** aims to provide researchers,professionals,and decision-makers with a thorough understanding of the existing privacy-preserving solutions in biometric recognition systems and serves as the foundation of the development of more secure and privacy-preserving biometric technologies.
Increasingly popular decentralized applications (dApps) with complex application logic incur significant overhead for executing smart contract transactions, which greatly limits public block chain performance. Pre-exe...
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