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Evolutionary Training of Deep Belief Networks for Handwritten Digit Recognition
Two of the most representative deep architectures are Deep Convolutional Neural Networks and Deep Belief Networks (DBNs).Both of these can be applied to the problem of pattern... -
Blood Vessel Analysis on High Resolution Fundus Retinal Images
Image analysis is a relevant tool to improve the healthcare services. Fundus retinal image analysis allows the early detection of ophthalmic diseases such as diabetes and... -
An evolutionary algorithm of linear complexity: application to training of de...
The performance of deep neural networks, such as Deep Belief Networks formed by Restricted Boltzmann Machines (RBMs), strongly depends on their training, which is the process of... -
Comparison of Parallel Versions of SA and GA for Optimizing the Performance o...
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving... -
Efficient training of deep learning models through improved adaptive sampling
Training of Deep Neural Networks (DNNs) is very computationally demanding and resources are typically spent on training-instances that do not provide the most benefit to a... -
Robust parameter estimation of a PEMFC via optimization based on probabilisti...
Recent developments in maintenance modelling fuelled by data-based approaches such as machine learning (ML), have enabled a broad range of applications. In the automotive... -
Homicide forecasting for the state of Guanajuato using LSTM and geospatial in...
In the last years, intentional homicides have increased significantly in Mexico. A proven strategy to confront the problem is applying predictive methods used to anticipate the... -
Improving Geomorphological Classification via Binary Image Processing
Landform classification is the basis for understanding and describing the processes and evolution of landscape. This process usually requires elevation information from... -
Improved training of deep convolutional networks via minimum-variance regular...
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated applications, but the outcomes of many AI models are challenging to comprehend and... -
Feature Analysis for Urban-land Change of Morelia City Via the TOC Curve
The feature analysis for feature selection is an important step for defining the inputs of the simulation models for urban growth. The simulation models are valuable tools for... -
Valley Classification using Convolutional Neural Network and a Geomorphons Map
Geomorphological classification serves as a valuable tool for comprehending the origin and evolution of landscapes, as well as for making informed decisions regarding... -
Enhancing Epidemic Prediction Using Simulated Annealing for Parameter Optimiz...
Understanding and predicting outbreaks of epidemics has become a major focus since COVID-19. Researchers have explored various methods, from basic curve fitting to complex... -
Exploring the gravitational model for ranking influential nodes in directed a...
In Social Network Analysis (SNA), the application of Directed Acyclic Graphs (DAGs) provides unique opportunities to explore structures where relationships have direction and do...
