6 citations · 7 across the 4 of their papers we have counts for
8 papers
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…
Deep Learning based Automated Forest Health Diagnosis from Aerial Images
Chia-Yen Chiang, Chloe Barnes, Plamen Angelov +1
Global climate change has had a drastic impact on our environment. Previous study showed that pest disaster occured from global climate change may cause a tremendous number of tree…
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…
A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion
Xiaowei Gu, Muhammad Aurangzeb Khan, Plamen Angelov +3
A novel self-organizing fuzzy proportional-integral-derivative (SOF-PID) control system is proposed in this paper. The proposed system consists of a pair of control and reference m…
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…