Gradient methods subject images to a series of operations enhance some characteristics and facilitate image analysis, usually the contours large objects. We argue that gradient must show other characteristics, such as minor components uniform regions, particularly for segmentation task where subjective concepts region coherence similarity are hard interpret from pixel information. This work ext...

As Artificial Intelligence (AI) is used in more applications, the need to consider and mitigate biases from learned models has followed. Most works developing fair learning algorithms focus on offline setting. However, many real-world applications data comes an online fashion needs be processed fly. Moreover, practical application, there a trade-off between accuracy fairness that accounted for,...

K-nearest neighbor (kNN) search is an important problem in data mining and knowledge discovery. Inspired by the huge success of tree-based methodology ensemble methods over last decades, we propose a new method for kNN search, random projection forests (rpForests). rpForests finds nearest neighbors combining multiple kNN-sensitive trees with each constructed recursively through series projectio...

This paper promotes the use of random forests as versatile tools for estimating spatially disaggregated indicators in presence small area-specific sample sizes. Small area estimators are predominantly conceptualized within regression-setting and rely on linear mixed models to account hierarchical structure survey data. In contrast, machine learning methods offer non-linear non-parametric altern...

Haptics, as well as force and torque measurements, are increasingly gaining attention in the fields of kinesthetic learning and robot Learning from Demonstration (LfD). For such learning techniques, it is essential to obtain accurate force and torque measurements in order to enable accurate control. However, force and torque measurements using a 6-axis force and torque sensor mounted at the end...

Automatic facial expression classification (FER) from videos is a critical problem for the development of intelligent human-computer interaction systems. Still, it is a challenging problem that involves capturing high-dimensional spatio-temporal patterns describing the variation of one’s appearance over time. Such representation undergoes great variability of the facial morphology and environme...

One of the important issues of machine learning is obtaining essential information from high-dimensional data for discrimination. Dimensionality reduction is a means to reduce the burden of dimensionality due to large-scale data. Feature selection determines significant variables and contributes to dimensionality reduction. In recent years, the random forests method has been the focus of resear...