9 papers
Feature extraction for plant growth estimation
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie H. Davel
Precision agriculture requires the estimation of plant growth stages in real-time. When the plant growth stage is known, the wastage of resources in cultivation, such as nutrients…
REACH: Interpretability-Driven Feature Identification and Architecture Compression for Multi-Channel Vehicular Channel Estimation
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie H. Davel
Multi-channel mixed-SNR training improves out-of-distribution (OOD) generalisation of deep learning channel estimators for IEEE 802.11p vehicular communications, yet the internal m…
Simplified Temporal Convolutional-Based Channel Estimation for a WiFi Vehicular Communication Channel
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie Davel
Channel estimation in vehicular communication is a crucial element in the advancement of intelligent transportation systems. However, the use of pilot signals in the IEEE 802.11p s…
KnowIt: Deep Time Series Modeling and Interpretation
M. W. Theunissen, R. Rabe, H. L. Potgieter +1
KnowIt (Knowledge discovery in time series data) is a flexible framework for building deep time series models and interpreting them. It is implemented as a Python toolkit, with sou…
Does simple trump complex? Comparing strategies for adversarial robustness in DNNs
William Brooks, Marelie H. Davel, Coenraad Mouton
Deep Neural Networks (DNNs) have shown substantial success in various applications but remain vulnerable to adversarial attacks. This study aims to identify and isolate the compone…
Impact of Batch Normalization on Convolutional Network Representations
Hermanus L. Potgieter, Coenraad Mouton, Marelie H. Davel
Batch normalization (BatchNorm) is a popular layer normalization technique used when training deep neural networks. It has been shown to enhance the training speed and accuracy of…