87 citations · 375 across the 43 of their papers we have counts for
6 papers · 1 filter
REDAR: Reinforcement-Driven Adaptive Regularisation for Class Incremental Learning
Akila Ayanthi, Darshana Priyasad, Tharindu Fernando +3
Regularisation-based class-incremental learning (CIL) methods control the stability-plasticity trade-off through fixed coefficients tuned offline, independently of the continual le…
Transforming volcanic monitoring: A dataset and benchmark for onboard volcano activity detection
Darshana Priyasad, Tharindu Fernando, Maryam Haghighat +2
Natural disasters, such as volcanic eruptions, pose significant challenges to daily life and incur considerable global economic losses. The emergence of next-generation small-satel…
Deep Learning for Medical Anomaly Detection -- A Survey
Tharindu Fernando, Harshala Gammulle, Simon Denman +2
Machine learning-based medical anomaly detection is an important problem that has been extensively studied. Numerous approaches have been proposed across various medical applicatio…
Memory based fusion for multi-modal deep learning
Darshana Priyasad, Tharindu Fernando, Simon Denman +2
The use of multi-modal data for deep machine learning has shown promise when compared to uni-modal approaches with fusion of multi-modal features resulting in improved performance…
Memory Augmented Deep Generative models for Forecasting the Next Shot Location in Tennis
Tharindu Fernando, Simon Denman, Sridha Sridharan +1
This paper presents a novel framework for predicting shot location and type in tennis. Inspired by recent neuroscience discoveries we incorporate neural memory modules to model the…
Tree Memory Networks for Modelling Long-term Temporal Dependencies
Tharindu Fernando, Simon Denman, Aaron McFadyen +2
In the domain of sequence modelling, Recurrent Neural Networks (RNN) have been capable of achieving impressive results in a variety of application areas including visual question a…