Computational intelligence and neuroscience
Jul 31, 2022
To improve the development level of intelligent dance education and choreography network technology, the research mainly focuses on the automatic formation system of continuous choreography by using the deep learning method. Firstly, it overcomes the...
Computational intelligence and neuroscience
Jul 30, 2022
This article analyzes the difficulties associated with the preservation and transmission of religious cultural resources and the difficulties encountered in the new development environment and background. It does so in light of the current state of r...
The effective estimation of mixed-layer depth (MLD) plays a significant role in the study of ocean dynamics and global climate change. However, the methods of estimating MLD still have limitations due to the sparse resolution of the observed data. In...
BACKGROUND: The discovery of critical biomarkers is significant for clinical diagnosis, drug research and development. Researchers usually obtain biomarkers from microarray data, which comes from the dimensional curse. Feature selection in machine le...
Explaining the diversity and complexity of protein localization is essential to fully understand cellular architecture. Here we present cytoself, a deep-learning approach for fully self-supervised protein localization profiling and clustering. Cytose...
Computational intelligence and neuroscience
Jul 21, 2022
A genetic disorder is a serious disease that affects a large number of individuals around the world. There are various types of genetic illnesses, however, we focus on mitochondrial and multifactorial genetic disorders for prediction. Genetic illness...
Journal of chemical theory and computation
Jul 20, 2022
We introduce an unsupervised clustering algorithm to improve training efficiency and accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML). This work determines clusters via the Gaussian mixture model (GMM) in an ent...
In this article, we elaborate on a Kullback-Leibler (KL) divergence-based Fuzzy C -Means (FCM) algorithm by incorporating a tight wavelet frame transform and morphological reconstruction (MR). To make membership degrees of each image pixel closer to ...
This article explores the problem of semisupervised affinity matrix learning, that is, learning an affinity matrix of data samples under the supervision of a small number of pairwise constraints (PCs). By observing that both the matrix encoding PCs, ...
Computational intelligence and neuroscience
Jul 16, 2022
In order to improve the reference value of film review data, this paper combines clustering analysis technology to construct a film review clustering visualization research system to improve the visualization effect of film reviews. Moreover, this pa...
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