TThis study uses the Vision Transformer (ViT) architecture to present a sophisticated approach for brain tumor identification and classification. ViT models are assessed based on their capacity to extract global conte...
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Sign language enhances the communication capabilities of the deaf-mute community, allowing for a deeper understanding of their needs and emotions. These languages are highly structured and visual, using gestures and v...
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Several of the environmental characteristics we hold dear, including our fundamental ecology, regional climatic variances, and global variety, are threatened caused by widespread industry and increasing urbanization. ...
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Progress in wisdom medicine has been driven by advancements in big data, cloud computing, and artificial intelligence, enabling the accumulation of valuable information and insights. However, the increasing reliance o...
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A chest X-ray is a common diagnostic tool for many thoracic illnesses. Interpreting these images and coming up with accurate diagnostic results is a difficult and time-consuming task for radiologists. Recent results u...
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Internet of Things connectivity in home health monitoring is a high-in-demand application area. The electronics industry and procedural researchers seek high-end, secured, on-time, cost-effective ways to build reliabl...
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In the fields of computer vision and gesture recognition, Recognizing Kuchipudi mudras in the real time, a traditional Indian dance form, is one of the challenging tasks. In this research work, an innovative solution ...
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Music recommendation systems have evolved from simple playlist curation techniques to sophisticated AI-driven models capable of analyzing human emotions for personalized song suggestions. Emotion-based music recommend...
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Feature extraction is pivotal in bioinformatics as it converts variable-length genome sequences into fixed-length mathematical feature vectors, which serve as input for clustering algorithms to cluster similar sequenc...
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Feature extraction is pivotal in bioinformatics as it converts variable-length genome sequences into fixed-length mathematical feature vectors, which serve as input for clustering algorithms to cluster similar sequences. One of the types of genome sequences is the Single Nucleotide Polymorphism (SNP), which categorises individuals into risk categories for plant diseases and predicts treatment outcomes more reliably. Extracting features from SNP sequences poses many challenges, including extracting similar features for distinct sequences and lacking context-based features. These approaches also take enormous time to compute features for a huge amount of SNP sequences. Therefore, a scalable approach to extract features is proposed based on a complex network, which converts the genome sequence into a complex network and extracts the proposed relevant features. The time utilised to extract those features has reduced drastically. The efficacy of the proposed scalable feature extraction approach is evaluated by applying K-means and Fuzzy c-means algorithms to assess the performance of this proposed feature vector set and found promising results when compared with the other alignment-free state-of-the-art approaches for feature extraction in terms of the Silhouette index and the Calinski–Harabasz index. Additionally, as most SNP datasets are unlabeled, determining the optimal number of clusters presents another significant challenge. A scalable algorithm called the S-MaxMin algorithm is proposed based on the distance metric to find the optimal number of clusters. The proposed S-MaxMin algorithm is being tested on different datasets, including eight labelled benchmark datasets, giving the same number of clusters as the actual number of classes. Also, the S-MaxMin algorithm is tested on four unlabeled SNP datasets, which yielded approximately the same number of clusters as the clusters with a high Silhouette index score. The two proposed scalable approaches are integrated in
High reliance on autonomous systems necessitates efficient and reliable data exchange through Vehicle-to-Infrastructure (V2I) communication to have appropriate and stable network performance in dynamic vehicular envir...
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