Search
Search Results
-
A Study on Different Deep Learning Algorithms Used in Deep Neural Nets: MLP SOM and DBN
Deep learning is a wildly popular topic in machine learning and is structured as a series of nonlinear layers that learns various levels of data...
-
Applications of Quantum Embedding in Computer Vision
Nowadays, Deep Neural Networks (DNNs) are fundamental to many vision tasks, including large-scale visual recognition. As the primary goal of the DNNs...
-
Comparison of hierarchical clustering and neural network clustering: an analysis on precision dominance
A comparison of neural network clustering (NNC) and hierarchical clustering (HC) is conducted to assess computing dominance of two machine learning...
-
Deep learning models beyond temporal frame-wise features for hand gesture video recognition
Recurrent neural networks (RNNs) are widely utilized in neural network research to capture spatiotemporal features in video data. However, their...
-
Patterns of infant fecal metabolite concentrations and social behavioral development in toddlers
BackgroundGut-derived metabolites, products of microbial and host co-metabolism, may inform mechanisms underlying children’s neurodevelopment. We...
-
Self-organization, quality control, and preclinical studies of human iPSC-derived retinal sheets for tissue-transplantation therapy
Three-dimensional retinal organoids (3D-retinas) are a promising graft source for transplantation therapy. We previously developed self-organizing...
-
Using Self-Organizing Maps for the Behavioral Analysis of Virtualized Network Functions
Detecting anomalous behaviors in a network function virtualization infrastructure is of the utmost importance for network operators. In this paper,...
-
Self-organizing Maps for Optimized Robotic Trajectory Planning Applied to Surface Coating
The process of surface coating is widely applied in the manufacturing industry. The accuracy of coating strongly affects the mechanical properties of...
-
Novel computational model of gastrula morphogenesis to identify spatial discriminator genes by self-organizing map (SOM) clustering
Deciphering the key mechanisms of morphogenesis during embryonic development is crucial to understanding the guiding principles of the body plan and...
-
Visual Monitoring of Industrial Operation States Based on Kernel Fisher Vector and Self-organizing Map Networks
As industrial process becomes increasingly complicated and the correlation between industrial process variables tends to exhibit strong nonlinear...
-
Establishing the original order of the poems in Harward’s Almanac using paleography, codicology, X-ray fluorescence spectroscopy, and statistical analysis
This work presents the results of a transdisciplinary analysis performed on Harward’s Almanac (Dublin, 1666), an extremely rare volume currently...
-
Root Cause Analysis for Self-organizing Cellular Network: an Active Learning Approach
To ease the configuration and maintenance of complex cellular networks, the self-organizing network (SON) is introduced. SON contains three major...
-
Clustering micropollutants and estimating rate constants of sorption and biodegradation using machine learning approaches
Effluent from wastewater treatment plants is considered an important source of micropollutants (MPs) in aquatic environments. However, monitoring MPs...
-
WiP: Distributed Intrusion Detection System for TCP/IP-Based Connections in Industrial Environments Using Self-organizing Maps
Digitization of the industry comes along with improvements for modern production, because the processes can be influenced, monitored and coordinated....
-
Intelligent wood machining monitoring using vibration signals combined with self-organizing maps for automatic feature selection
Data-driven models were developed for monitoring the power consumption and wood quality during the lumber manufacturing process. The study proposes...
-
Semantic embedding based online cross-modal hashing method
Hashing has been extensively utilized in cross-modal retrieval due to its high efficiency in handling large-scale, high-dimensional data. However,...
-
Photonic integrated circuits based optimization and enhancing data transmission for radio access networks using machine learning model
By using edge caching and edge computing, fog radio access networks (F-RANs) are viewed as suitable architectures to serve Internet of Things...
-
Unsupervised Learning Neural Networks
This chapter introduces the basic concepts and notation of unsupervised learning neural networks. Unsupervised networks are useful for analyzing data...
-
Self-Organizing Maps
In PCA, the most outlying data points determine the direction of the PCs—these are the ones contributing most to the variance. This often results in...
-
Self-Organizing Maps with Convolutional Layers
Self-organizing maps (SOMs) are well appropriate for visualizing high-dimensional data sets. Training SOMs on raw high-dimensional data with classic...