Titlebook: Applied Intelligence; First International De-Shuang Huang,Prashan Premaratne,Changan Yuan Conference proceedings 2024 The Editor(s) (if ap

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書(shū)目名稱(chēng)Applied Intelligence影響因子(影響力)




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Carbon-Monoxide

RADE

Trigger-Point

Bradyrhizobium Elkanii’s Genes Classification with SVM magnified thousands or even tens of thousands of times to be observed. Bradyrhizobium elkanii’s is one of the most significant oral microorganisms. In this work, we focus on the classification of Bradyrhizobium elkanii’s coding genes and non-coding ones. We selected the whole genome information fro

Climate

Oral Lichen Planus Classification with SEResNetled of oral health. Such disease poses a serious threat to oral health. In this work, we focus on classification the oral lichen planus photos between pro-treatment and post-treatment. We selected 67 pro-treatment patients’ photos and 41 post-treatment patients’ photos. And then, we employed SEResNe

暗指

Nucleotide Sequence Classification of Paeonia Lactiflora Based on Feature Representation Learningde effects and better patient compliance. Nucleotide sequence is of great significance in the field of Botany. In order to further study the pharmacology of Radix Paeonia Alba, the classification and prediction of nucleotide sequence of Radix Paeonia Alba is an important challenge. In this paper, we

obstruct

Semantic Similarity Functions and Their Applicationsto Plato. Although studied by philosophers, and mathematicians for a long time, there was no agreement on the “best way” to define it and measure it. Recently, the concept of similarity and methods to assess similarity between objects have assumed great importance in Data Mining (DM), Machine Learni

存在主義

A Multi-Scale Spatiotemporal Capsule Network for Epilepsy Seizure Detectionsometimes lead to inconsistent judgment outcomes. To mitigate this, it is imperative to establish a comprehensive algorithm to aid in resolving this issue. This study introduces a novel deep learning architecture that integrates convolutional neural network (CNN) and capsule neural network (CapsNet)

CLEFT

Improved ConvNeXt Facial Expression Recognition Embedded with Attention Mechanismiving, intelligent monitoring, and human-computer interaction. This article addresses the problems of insufficient key information extraction, low recognition accuracy, and easy overfitting in facial expression recognition, and proposes an ECA-ConvNeXt network based on transfer learning strategy and

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