Machine Learning and Knowledge Extraction, Volume 2, Issue 3

We present a method to improve the reconstruction and generation performance of a variational autoencoder (VAE) by injecting an adversarial learning. Instead of comparing the reconstructed with the original data to calculate the reconstruction loss,...

Eating disorders are very complicated and many factors play a role in their manifestation. Furthermore, due to the variability in diagnosis and symptoms, treatment for an eating disorder is unique to the individual. As a result, there are numerous as...

For incremental machine-learning applications it is often important to robustly estimate the system accuracy during training, especially if humans perform the supervised teaching. Cross-validation and interleaved test/train error are here the standar...

In spatio-temporal predictive coding problems, like next-frame prediction in video, determining the content of plausible future frames is primarily based on the image dynamics of previous frames. We establish an alternative approach based on their un...

In this work, we developed a data-driven framework to predict near-surface (0–5 cm) soil moisture (SM) by mapping inputs from the Soil & Water Assessment Tool to SM time series from NASA’s Soil Moisture Active Passive (SMAP) satellite...

With the introduction of the Convolutional Neural Network (CNN) and other classical algorithms, facial and object recognition have made significant progress. However, in a situation where there are few label examples or the environment is not ideal,...

A Long Short Term Memory (LSTM) based sales model has been developed to forecast the global sales of hotel business of Travel Boutique Online Holidays (TBO Holidays). The LSTM model is a multivariate model; input to the model includes several indepen...

In the real world, structured data are increasingly represented by graphs. In general, the applications concern the most varied fields, and the data need to be represented in terms of local and spatial connections. In this scenario, the goal is to pr...

The proliferation of social media platforms changed the way people interact online. However, engagement with social media comes with a price, the users’ privacy. Breaches of users’ privacy, such as the Cambridge Analytica scandal, can rev...

File fragment classification is an essential problem in digital forensics. Although several attempts had been made to solve this challenging problem, a general solution has not been found. In this work, we propose a hierarchical machine-learning-base...

This research presents a machine vision approach to detect lesions in liver ultrasound as well as resolving some issues in ultrasound such as artifacts, speckle noise, and blurring effect. The anisotropic diffusion is modified using the edge preserva...

Increasing concerns about the prevalence of false information and fake news has led to calls for automated fact-checking systems that are capable of verifying the truthfulness of statements, especially on the internet. Most previous automated fact-ch...