Tharindu Fernando

DeepAI AI Chat

Featured Co-authors

Clinton Fookes
110 publications
Sridha Sridharan
90 publications
Lars Petersson
64 publications
Simon Denman
64 publications
Peyman Moghadam
31 publications
Kien Nguyen
24 publications
Harshala Gammulle
16 publications
David Ahmedt-Aristizabal
14 publications
Mitchell McLaren
10 publications
Houman Ghaemmaghami
4 publications
Theekshana Dissanayake
3 publications

research

∙ 09/18/2023

FactoFormer: Factorized Hyperspectral Transformers with Self-Supervised Pre-Training

Hyperspectral images (HSIs) contain rich spectral and spatial informatio...

0 Shaheer Mohamed, et al. ∙

research

∙ 05/19/2023

Remembering What Is Important: A Factorised Multi-Head Retrieval and Auxiliary Memory Stabilisation Scheme for Human Motion Prediction

Humans exhibit complex motions that vary depending on the task that they...

0 Tharindu Fernando, et al. ∙

research

∙ 05/01/2023

Physical Adversarial Attacks for Surveillance: A Survey

Modern automated surveillance techniques are heavily reliant on deep lea...

0 Kien Nguyen, et al. ∙

research

∙ 11/15/2022

Using Auxiliary Information for Person Re-Identification – A Tutorial Overview

Person re-identification (re-id) is a pivotal task within an intelligent...

0 Tharindu Fernando, et al. ∙

research

∙ 04/05/2022

Towards On-Board Panoptic Segmentation of Multispectral Satellite Images

With tremendous advancements in low-power embedded computing devices and...

0 Tharindu Fernando, et al. ∙

research

∙ 08/09/2021

Multi-Slice Net: A novel light weight framework for COVID-19 Diagnosis

This paper presents a novel lightweight COVID-19 diagnosis framework usi...

0 Harshala Gammulle, et al. ∙

research

∙ 06/30/2021

Robust and Interpretable Temporal Convolution Network for Event Detection in Lung Sound Recordings

This paper proposes a novel framework for lung sound event detection, se...

0 Tharindu Fernando, et al. ∙

research

∙ 12/04/2020

Deep Learning for Medical Anomaly Detection – A Survey

Machine learning-based medical anomaly detection is an important problem...

44 Tharindu Fernando, et al. ∙

research

∙ 11/18/2020

Patient-independent Epileptic Seizure Prediction using Deep Learning Models

Objective: Epilepsy is one of the most prevalent neurological diseases a...

12 Theekshana Dissanayake, et al. ∙

research

∙ 11/12/2020

Domain Generalization in Biosignal Classification

Objective: When training machine learning models, we often assume that t...

7 Theekshana Dissanayake, et al. ∙

research

∙ 11/10/2020

Fast Slow Learning: Incorporating Synthetic Gradients in Neural Memory Controllers

Neural Memory Networks (NMNs) have received increased attention in recen...

0 Tharindu Fernando, et al. ∙

research

∙ 09/23/2020

Attention Driven Fusion for Multi-Modal Emotion Recognition

Deep learning has emerged as a powerful alternative to hand-crafted meth...

0 Darshana Priyasad, et al. ∙

research

∙ 07/16/2020

Memory Based Attentive Fusion

The use of multi-modal data for deep machine learning has shown promise ...

0 Darshana Priyasad, et al. ∙

research

∙ 05/21/2020

Understanding the Importance of Heart Sound Segmentation for Heart Anomaly Detection

Traditionally, abnormal heart sound classification is framed as a three-...

0 Theekshana Dissanayake, et al. ∙

research

∙ 04/02/2020

Temporarily-Aware Context Modelling using Generative Adversarial Networks for Speech Activity Detection

This paper presents a novel framework for Speech Activity Detection (SAD...

0 Tharindu Fernando, et al. ∙

research

∙ 04/02/2020

Heart Sound Segmentation using Bidirectional LSTMs with Attention

This paper proposes a novel framework for the segmentation of phonocardi...

0 Tharindu Fernando, et al. ∙

research

∙ 12/10/2019

Neural Memory Networks for Seizure Type Classification

Classification of seizure type is a key step in the clinical process for...

0 David Ahmedt-Aristizabal, et al. ∙

research

∙ 12/10/2019

Neural Memory Networks for Robust Classification of Seizure Type

Classification of seizure type is a key step in the clinical process for...

0 David Ahmedt-Aristizabal, et al. ∙

research

∙ 11/17/2019

Exploiting Human Social Cognition for the Detection of Fake and Fraudulent Faces via Memory Networks

Advances in computer vision have brought us to the point where we have t...

0 Tharindu Fernando, et al. ∙

research

∙ 10/12/2019

Neural Memory Plasticity for Anomaly Detection

In the domain of machine learning, Neural Memory Networks (NMNs) have re...

0 Tharindu Fernando, et al. ∙

research

∙ 09/20/2019

Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation

We propose a novel conditional GAN (cGAN) model for continuous fine-grai...

0 Harshala Gammulle, et al. ∙

research

∙ 01/16/2019

Memory Augmented Deep Generative models for Forecasting the Next Shot Location in Tennis

This paper presents a novel framework for predicting shot location and t...

14 Tharindu Fernando, et al. ∙

research

∙ 12/18/2018

GD-GAN: Generative Adversarial Networks for Trajectory Prediction and Group Detection in Crowds

This paper presents a novel deep learning framework for human trajectory...

28 Tharindu Fernando, et al. ∙

research

∙ 07/22/2018

Pedestrian Trajectory Prediction with Structured Memory Hierarchies

This paper presents a novel framework for human trajectory prediction ba...

0 Tharindu Fernando, et al. ∙

research

∙ 05/14/2018

Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories

With the explosion in the availability of spatio-temporal tracking data ...

0 Tharindu Fernando, et al. ∙

research

∙ 05/13/2018

Learning Temporal Strategic Relationships using Generative Adversarial Imitation Learning

This paper presents a novel framework for automatic learning of complex ...

0 Tharindu Fernando, et al. ∙

research

∙ 03/09/2018

Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks

Visual saliency patterns are the result of a variety of factors aside fr...

0 Tharindu Fernando, et al. ∙

research

∙ 03/09/2018

Tracking by Prediction: A Deep Generative Model for Mutli-Person localisation and Tracking

Current multi-person localisation and tracking systems have an over reli...

0 Tharindu Fernando, et al. ∙

research

∙ 03/12/2017

Tree Memory Networks for Modelling Long-term Temporal Dependencies

In the domain of sequence modelling, Recurrent Neural Networks (RNN) hav...

0 Tharindu Fernando, et al. ∙

research

∙ 02/18/2017

Soft + Hardwired Attention: An LSTM Framework for Human Trajectory Prediction and Abnormal Event Detection

As humans we possess an intuitive ability for navigation which we master...

0 Tharindu Fernando, et al. ∙

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