Search Results for author: David Ahmedt-Aristizabal

Found 20 papers, 0 papers with code

Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation

no code implementations14 Apr 2024 Sam Cantrill, David Ahmedt-Aristizabal, Lars Petersson, Hanna Suominen, Mohammad Ali Armin

We demonstrate significant performance improvements of up to 29. 6% in all tested motion scenarios in cross-dataset testing on MMPD, even in the presence of dynamic and unconstrained subject motion, emphasizing the benefits of disentangling motion through modeling the 3D facial surface for motion robust facial rPPG estimation.

Deep Learning Approaches for Seizure Video Analysis: A Review

no code implementations18 Dec 2023 David Ahmedt-Aristizabal, Mohammad Ali Armin, Zeeshan Hayder, Norberto Garcia-Cairasco, Lars Petersson, Clinton Fookes, Simon Denman, Aileen McGonigal

Historically, these approaches have been used for disease detection, classification, and prediction using diagnostic data; however, there has been limited exploration of their application in evaluating video-based motion detection in the clinical epileptology setting.

Decision Making Motion Detection +1

Automated Coronary Arteries Labeling Via Geometric Deep Learning

no code implementations1 Dec 2022 Yadan Li, Mohammad Ali Armin, Simon Denman, David Ahmedt-Aristizabal

Automatic labelling of anatomical structures, such as coronary arteries, is critical for diagnosis, yet existing (non-deep learning) methods are limited by a reliance on prior topological knowledge of the expected tree-like structures.

graph construction

Vision-Based Activity Recognition in Children with Autism-Related Behaviors

no code implementations8 Aug 2022 Pengbo Wei, David Ahmedt-Aristizabal, Harshala Gammulle, Simon Denman, Mohammad Ali Armin

Advances in machine learning and contactless sensors have enabled the understanding complex human behaviors in a healthcare setting.

Activity Recognition

A Real-time Edge-AI System for Reef Surveys

no code implementations1 Aug 2022 Yang Li, Jiajun Liu, Brano Kusy, Ross Marchant, Brendan Do, Torsten Merz, Joey Crosswell, Andy Steven, Lachlan Tychsen-Smith, David Ahmedt-Aristizabal, Jeremy Oorloff, Peyman Moghadam, Russ Babcock, Megha Malpani, Ard Oerlemans

Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are ongoing to manage COTS populations to ecologically sustainable levels.

Computational Efficiency object-detection +1

Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging

no code implementations14 May 2022 David Ahmedt-Aristizabal, Chuong Nguyen, Lachlan Tychsen-Smith, Ashley Stacey, Shenghong Li, Joseph Pathikulangara, Lars Petersson, Dadong Wang

A modular camera rig arranged in a cylindrical configuration was designed to automatically capture images of the entire skin surface of a subject synchronously from multiple angles.

Image Reconstruction Lesion Detection +1

Continuous Human Action Recognition for Human-Machine Interaction: A Review

no code implementations26 Feb 2022 Harshala Gammulle, David Ahmedt-Aristizabal, Simon Denman, Lachlan Tychsen-Smith, Lars Petersson, Clinton Fookes

With advances in data-driven machine learning research, a wide variety of prediction models have been proposed to capture spatio-temporal features for the analysis of video streams.

Action Recognition Action Segmentation +4

Privacy-Preserving In-Bed Pose Monitoring: A Fusion and Reconstruction Study

no code implementations22 Feb 2022 Thisun Dayarathna, Thamidu Muthukumarana, Yasiru Rathnayaka, Simon Denman, Chathura de Silva, Akila Pemasiri, David Ahmedt-Aristizabal

In this paper we explore the effective use of images from multiple non-visual and privacy-preserving modalities such as depth, long-wave infrared (LWIR) and pressure maps for the task of in-bed pose estimation in two settings.

Generative Adversarial Network Pose Estimation +1

The CSIRO Crown-of-Thorn Starfish Detection Dataset

no code implementations29 Nov 2021 Jiajun Liu, Brano Kusy, Ross Marchant, Brendan Do, Torsten Merz, Joey Crosswell, Andy Steven, Nic Heaney, Karl Von Richter, Lachlan Tychsen-Smith, David Ahmedt-Aristizabal, Mohammad Ali Armin, Geoffrey Carlin, Russ Babcock, Peyman Moghadam, Daniel Smith, Tim Davis, Kemal El Moujahid, Martin Wicke, Megha Malpani

Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are underway in an attempt to manage COTS populations to ecologically sustainable levels.

BIG-bench Machine Learning Management

A Survey on Graph-Based Deep Learning for Computational Histopathology

no code implementations1 Jul 2021 David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson

With the remarkable success of representation learning for prediction problems, we have witnessed a rapid expansion of the use of machine learning and deep learning for the analysis of digital pathology and biopsy image patches.

graph construction Image Retrieval +4

Towards Interpretable Attention Networks for Cervical Cancer Analysis

no code implementations27 May 2021 Ruiqi Wang, Mohammad Ali Armin, Simon Denman, Lars Petersson, David Ahmedt-Aristizabal

Here, we evaluate various state-of-the-art deep learning models and attention-based frameworks for the classification of images of multiple cervical cells.


Neural Memory Networks for Seizure Type Classification

no code implementations10 Dec 2019 David Ahmedt-Aristizabal, Tharindu Fernando, Simon Denman, Lars Petersson, Matthew J. Aburn, Clinton Fookes

Inspired by recent advances in neural memory networks (NMNs), we introduce a novel approach for the classification of seizure type using electrophysiological data.

Classification EEG +3

Neural Memory Plasticity for Anomaly Detection

no code implementations12 Oct 2019 Tharindu Fernando, Simon Denman, David Ahmedt-Aristizabal, Sridha Sridharan, Kristin Laurens, Patrick Johnston, Clinton Fookes

In the domain of machine learning, Neural Memory Networks (NMNs) have recently achieved impressive results in a variety of application areas including visual question answering, trajectory prediction, object tracking, and language modelling.

Anomaly Detection EEG +6

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