Titlebook: Recent Advances in Artificial Intelligence and Smart Applications; Proceedings of RAAIS Jyotsna Kumar Mandal,Mike Hinchey,Satyajit Chakrab

Pelvic-Floor

Improving Uniqueness of Named Entities with Knowledge-Based Textual Enrichment in Automatic Questioties. Knowledge enrichment is carried out based on FAIR principles in the proposed work to generate semantically rich questions. Experiments show that the proposed work avoids redundancy by generating more number of questions with relative increase in the size of uniquely expanded entity set.

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,Design a?COVID-19 Vaccination Status Verification System Using Face Recognition for?Bangladesh,ern (LBP) algorithm is used for facial matching. A string matching algorithm correlates the NID number, enabling smooth retrieval of vaccination history. The paper explains the process, including NID retrieval, facial matching, and data extraction. This approach streamlines vaccine verification and supports epidemic control efforts.

含鐵

Multisensor-Based Multitasking Goggles to Reduce Road Accidents, to recover from such intense workload. As a consequence, there is a rapid increase in car accidents. While various factors contribute to car accidents, driver drowsiness is the leading cause. Driver drowsiness is a huge problem nowadays, and it is not an unknown fact everyone knows about, but only

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Secured Assertive Protocol for Routing in Cloud Network,ternet to a large group of users. This ecosystem may be shared at any level and is available worldwide via the Internet. A diverse set of clients may be bartered with in exchange for various resources, infrastructure, and platforms. Accessing servers from afar is made possible by CC. Data virtualiza

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Capturing Moments: An AI-Powered Image Captioning System, integrates knowledge of computer vision with natural language processing. This task has numerous applications in fields such as robotics, human–computer interaction, and multimedia content analysis. Most images have little captions, but we can still understand them in large part without them. So, w

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Improving Uniqueness of Named Entities with Knowledge-Based Textual Enrichment in Automatic Questios on the generation of aware semantic questions. Various natural language processing techniques are available to perform the text to question transformation to fill the gaps. Here the challenge is to bring out the semantic richness in automatic question generation. The solution has been proposed by

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Comparative Analysis of Pre-trained Deep Learning Models for Cataract Detection in Color Fundus Imamal eyes using color fundus images. The models under consideration include VGG16, VGG19, InceptionV3, DenseNet121, DenseNet201, MobileNet, MobileNetV2, ResNet50, and ResNet152. Through rigorous experimentation and analysis, we evaluate the models’ training, validation, and testing accuracies to gaug