BenchMetrics Prob: benchmarking of probabilistic error/loss performance evaluation instruments for binary classification problems [0.03%]
二元分类问题的概率错误/损失性能评估工具的基准测试问题
Gürol Canbek
Gürol Canbek
Probabilistic error/loss performance evaluation instruments that are originally used for regression and time series forecasting are also applied in some binary-class or multi-class classifiers, such as artificial neural networks. This study...
ICUnet++: an Inception-CBAM network based on Unet++ for MR spine image segmentation [0.03%]
基于Inception-CBAM网络的UNET++医学脊椎MR图像分割模型(ICUNet++)
Lei Li,Juan Qin,Lianrong Lv et al.
Lei Li et al.
In recent years, more attention paid to the spine caused by related diseases, spinal parsing (the multi-class segmentation of vertebrae and intervertebral disc) is an important part of the diagnosis and treatment of various spinal diseases....
A three-way decisions approach based on double hierarchy linguistic aggregation operators of strict t-norms and t-conorms [0.03%]
基于严格t-范数和t余范数双层次语言聚合算子的三支决策方法
Yihua Zhong,Ping Wu,Chuan Chen et al.
Yihua Zhong et al.
With the massive increase in uncertainty of linguistic information in realistic decision making, there is a great challenge for people to make decisions in the complex linguistic environment. To overcome this challenge, this paper proposes ...
Yuantao Chen,Runlong Xia,Ke Zou et al.
Yuantao Chen et al.
In the last few years, image inpainting methods based on deep learning models had shown obvious advantages compared with existing traditional methods. The former can better generate visually reasonable image structure and texture informatio...
Optimal interventional policy based on discrete-time fuzzy rules equivalent model utilizing with COVID-19 pandemic data [0.03%]
基于离散时间模糊规则等效模型的最优干预政策（利用COVID-19大流行数据）
C Treesatayapun
C Treesatayapun
In this paper, a mathematical model of the COVID-19 pandemic is formulated by fitting it to actual data collected during the fifth wave of the COVID-19 pandemic in Coahuila, Mexico, from June 2022 to October 2022. The data sets used are rec...
SecureFed: federated learning empowered medical imaging technique to analyze lung abnormalities in chest X-rays [0.03%]
安全的联邦学习赋能医学影像技术以分析胸部X光片中的肺部异常状况
Aaisha Makkar,K C Santosh
Aaisha Makkar
Machine learning is an effective and accurate technique to diagnose COVID-19 infections using image data, and chest X-Ray (CXR) is no exception. Considering privacy issues, machine learning scientists end up receiving less medical imaging d...
A novel framework based on the multi-label classification for dynamic selection of classifiers [0.03%]
基于多标签分类的动态选择分类器的新框架
Javad Elmi,Mahdi Eftekhari,Adel Mehrpooya et al.
Javad Elmi et al.
Multi-classifier systems (MCSs) are some kind of predictive models that classify instances by combining the output of an ensemble of classifiers given in a pool. With the aim of enhancing the performance of MCSs, dynamic selection (DS) tech...
Yuxiang Yang,Xing Tian,Wing W Y Ng et al.
Yuxiang Yang et al.
COVID-19 has resulted in a significant impact on individual lives, bringing a unique challenge for face retrieval under occlusion. In this paper, an occluded face retrieval method which consists of generator, discriminator, and deep hashing...
Multilevel hybrid accurate handcrafted model for myocardial infarction classification using ECG signals [0.03%]
使用ECG信号进行心肌梗塞分类的多级混合精确手工模型
Prabal Datta Barua,Emrah Aydemir,Sengul Dogan et al.
Prabal Datta Barua et al.
Myocardial infarction (MI) is detected using electrocardiography (ECG) signals. Machine learning (ML) models have been used for automated MI detection on ECG signals. Deep learning models generally yield high classification performance but ...
Jie Wen,Zhixia Zhang,Yang Lan et al.
Jie Wen et al.
Federated learning (FL) is a secure distributed machine learning paradigm that addresses the issue of data silos in building a joint model. Its unique distributed training mode and the advantages of security aggregation mechanism are very s...