This paper proposes an implementation method for an autonomous art exhibition system using open-source hardware. The proposed method measures the time spent viewing artworks that catch the user's eye, identifies t...
详细信息
Subspace clustering, known for its effectiveness in handling high-dimensional data, has attracted attention. And the autoencoder can discover hidden features within a large dataset, yet it faces challenges in utilizin...
详细信息
The electrocardiogram (ECG) is an essential diagnostic tool for monitoring heart health. Traditional manual methods for ECG interpretation are increasingly challenged by the complexity of heart diseases and the volume...
详细信息
In this paper, we proposed a convolutional neural network based on EEGNet, which can be used to classify the degree of fatigue, without manual feature extraction, and directly take the original EEG as input, and the r...
详细信息
Source-free domain adaptation (SFDA) has gained significant attention as a method to transfer knowledge from a pre-trained model on source domains toward target domains without accessing the source data. Recent resear...
详细信息
Web scraping is a powerful technique that extracts data from websites, enabling automated data collection, enhancing data analysis capabilities, and minimizing manual data entry efforts. Existing methods, wrappers-bas...
详细信息
Mohan et *** a feed-forward neural network(FFNN)model to predict Kamlet-Taft parameters using quantum chemically derived features,achieving notable predictive ***,this study raises concerns about conflating prediction...
详细信息
Mohan et *** a feed-forward neural network(FFNN)model to predict Kamlet-Taft parameters using quantum chemically derived features,achieving notable predictive ***,this study raises concerns about conflating prediction accuracy with feature importance accuracy,as high R^(2)and low root mean square error(RMSE)do not guarantee valid feature importance *** reliance on SHapley Additive exPlanations(SHAP)for feature evaluation is problematic due to model-specific biases that could misrepresent true associations.A broader understanding of data distribution,statistical relationships,and significance testing through pvalues is essential to rectify *** paper advocates for employing robust statistical methods,like Spearman's correlation,to effectively assess genuine associations and mitigate biases in feature importance analysis.
This paper proposes an application of the Automated Deep Learning model to predict the presence of olive flies in crops. Compared to baseline algorithms such as Random Forest or K-Nearest Neighbor, our Automated Deep ...
详细信息
It is well known that eigenfunctions of a kernel play a crucial role in kernel regression. Through several examples, we demonstrate that even with the same set of eigenfunctions, the order of these functions significa...
In this paper, we propose a novel tensor completion framework, Overlapping Tensor Train Completion with TV Regularization (OTTC-TV), which integrates the strengths of both Overlapping Ket Augmentation (OKA) and Total ...
详细信息
暂无评论