Global bibliometric mapping of the frontier of knowledge in the field of artificial intelligence for the period 1990-2019 [0.03%]
1990-2019年人工智能领域前沿知识的全球文献计量地图研究
Iván Manuel De la Vega Hernández,Angel Serrano Urdaneta,Elias Carayannis
Iván Manuel De la Vega Hernández
Artificial Intelligence (AI) has emerged as a field of knowledge that is displacing and disrupting technologies, leading to changes in human life. Therefore, the purpose of this study is to scientifically map this topic and its ramification...
A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches [0.03%]
微organisms图像分析中目标检测技术的研究进展：从传统方法到深度学习方案
Pingli Ma,Chen Li,Md Mamunur Rahaman et al.
Pingli Ma et al.
Microorganisms play a vital role in human life. Therefore, microorganism detection is of great significance to human beings. However, the traditional manual microscopic detection methods have the disadvantages of long detection cycle, low d...
A survey on the use of association rules mining techniques in textual social media [0.03%]
关联规则在文本社交媒体中的挖掘技术使用调查综述
Jose A Diaz-Garcia,M Dolores Ruiz,Maria J Martin-Bautista
Jose A Diaz-Garcia
The incursion of social media in our lives has been much accentuated in the last decade. This has led to a multiplication of data mining tools aimed at obtaining knowledge from these data sources. One of the greatest challenges in this area...
Applications of artificial neural networks in microorganism image analysis: a comprehensive review from conventional multilayer perceptron to popular convolutional neural network and potential visual transformer [0.03%]
人工神经网络在微生物图像分析中的应用：从传统的多层感知器到流行的卷积神经网络和潜在的视觉转换器的全面回顾
Jinghua Zhang,Chen Li,Yimin Yin et al.
Jinghua Zhang et al.
Microorganisms are widely distributed in the human daily living environment. They play an essential role in environmental pollution control, disease prevention and treatment, and food and drug production. The analysis of microorganisms is e...
Developments in the detection of diabetic retinopathy: a state-of-the-art review of computer-aided diagnosis and machine learning methods [0.03%]
糖尿病视网膜病变检测的新进展：计算机辅助诊断和机器学习方法的现状及展望研究
Ganeshsree Selvachandran,Shio Gai Quek,Raveendran Paramesran et al.
Ganeshsree Selvachandran et al.
The exponential increase in the number of diabetics around the world has led to an equally large increase in the number of diabetic retinopathy (DR) cases which is one of the major complications caused by diabetes. Left unattended, DR worse...
Deep Neuro-Fuzzy System application trends, challenges, and future perspectives: a systematic survey [0.03%]
深度神经模糊系统应用趋势、挑战及未来前景：系统性调查研究报告
Noureen Talpur,Said Jadid Abdulkadir,Hitham Alhussian et al.
Noureen Talpur et al.
Deep neural networks (DNN) have remarkably progressed in applications involving large and complex datasets but have been criticized as a black-box. This downside has recently become a motivation for the research community to pursue the idea...
Mourtadha Badiane,Pádraig Cunningham
Mourtadha Badiane
There exist a variety of distance measures which operate on time series kernels. The objective of this article is to compare those distance measures in a support vector machine setting. A support vector machine is a state-of-the-art classif...
A new fusion of whale optimizer algorithm with Kapur's entropy for multi-threshold image segmentation: analysis and validations [0.03%]
一种新的融合鲸鱼优化算法与Kapur熵的多阈值图像分割方法：分析与验证
Mohamed Abdel-Basset,Reda Mohamed,Mohamed Abouhawwash
Mohamed Abdel-Basset
The separation of an object from other objects or the background by selecting the optimal threshold values remains a challenge in the field of image segmentation. Threshold segmentation is one of the most popular image segmentation techniqu...
Modality specific U-Net variants for biomedical image segmentation: a survey [0.03%]
医学图像分割的模态特定U型网络变体：综述
Narinder Singh Punn,Sonali Agarwal
Narinder Singh Punn
With the advent of advancements in deep learning approaches, such as deep convolution neural network, residual neural network, adversarial network; U-Net architectures are most widely utilized in biomedical image segmentation to address the...
AI-aided general clinical diagnoses verified by third-parties with dynamic uncertain causality graph extended to also include classification [0.03%]
基于第三方验证的动态不确定因果关系图的辅助通用临床诊断及其分类扩展
Zhan Zhang,Yang Jiao,Mingxia Zhang et al.
Zhan Zhang et al.
Artificial intelligence (AI)-aided general clinical diagnosis is helpful to primary clinicians. Machine learning approaches have problems of generalization, interpretability, etc. Dynamic Uncertain Causality Graph (DUCG) based on uncertain ...