87 citations · 104 across the 6 of their papers we have counts for
7 papers
Position Paper on Dataset Engineering to Accelerate Science
Emilio Vital Brazil, Eduardo Soares, Lucas Villa Real +4
Data is a critical element in any discovery process. In the last decades, we observed exponential growth in the volume of available data and the technology to manipulate it. Howeve…
An Interpretable Deep Semantic Segmentation Method for Earth Observation
Ziyang Zhang, Plamen Angelov, Eduardo Soares +2
Earth observation is fundamental for a range of human activities including flood response as it offers vital information to decision makers. Semantic segmentation plays a key role…
Towards Deep Machine Reasoning: a Prototype-based Deep Neural Network with Decision Tree Inference
Plamen Angelov, Eduardo Soares
In this paper we introduce the DMR -- a prototype-based method and network architecture for deep learning which is using a decision tree (DT)-based inference and synthetic data to…
Towards Explainable Deep Neural Networks (xDNN)
Plamen Angelov, Eduardo Soares
In this paper, we propose an elegant solution that is directly addressing the bottlenecks of the traditional deep learning approaches and offers a clearly explainable internal arch…
A Self-Adaptive Synthetic Over-Sampling Technique for Imbalanced Classification
Xiaowei Gu, Plamen P Angelov, Eduardo Almeida Soares
Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50% to 80%) is used for training and the rest for validation. In many problems, h…
Novelty Detection and Learning from Extremely Weak Supervision
Eduardo Soares, Plamen Angelov
In this paper we offer a method and algorithm, which make possible fully autonomous (unsupervised) detection of new classes, and learning following a very parsimonious training pri…