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Found 23 papers, 6 papers with code
Developing Normative Gait Cycle Parameters for Clinical Analysis Using Human Pose Estimation
Despite its promise, current applications using RGB video data alone are limited in measuring clinically relevant spatial and temporal kinematics and establishing normative parameters essential for identifying movement abnormalities within a gait cycle.
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video Dataset
We introduce The Gait Abnormality in Video Dataset (GAVD) in response to our review of over 150 current gait-related computer vision datasets, which highlighted the need for a large and accessible gait dataset clinically annotated for CGA.
Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation
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
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.
Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis
Wound management poses a significant challenge, particularly for bedridden patients and the elderly.
A Hyperspectral and RGB Dataset for Building Facade Segmentation
Hyperspectral Imaging (HSI) provides detailed spectral information and has been utilised in many real-world applications.
Automated Coronary Arteries Labeling Via Geometric Deep Learning
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.
Vision-Based Activity Recognition in Children with Autism-Related Behaviors
Advances in machine learning and contactless sensors have enabled the understanding complex human behaviors in a healthcare setting.
You Only Cut Once: Boosting Data Augmentation with a Single Cut
We present You Only Cut Once (YOCO) for performing data augmentations.
In-Bed Human Pose Estimation from Unseen and Privacy-Preserving Image Domains
Medical applications have benefited greatly from the rapid advancement in computer vision.
The CSIRO Crown-of-Thorn Starfish Detection Dataset
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.
Learning To Segment Dominant Object Motion From Watching Videos
Existing deep learning based unsupervised video object segmentation methods still rely on ground-truth segmentation masks to train.
Declarative nets that are equilibrium models
We show that using a kernelised generalised linear model (kGLM) as an inner problem in a DDN yields a large class of commonly used DEQ architectures with a closed-form expression for the hidden layer parameters in terms of the kernel.
Blind Image Decomposition
We propose and study a novel task named Blind Image Decomposition (BID), which requires separating a superimposed image into constituent underlying images in a blind setting, that is, both the source components involved in mixing as well as the mixing mechanism are unknown.
A Survey on Graph-Based Deep Learning for Computational Histopathology
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.
Underwater Image Restoration via Contrastive Learning and a Real-world Dataset
There are 2000 reference restored images and 6003 original underwater images in the unpaired training set.
Video-Based Inpatient Fall Risk Assessment: A Case Study
Inpatient falls are a serious safety issue in hospitals and healthcare facilities.
Towards Interpretable Attention Networks for Cervical Cancer Analysis
Here, we evaluate various state-of-the-art deep learning models and attention-based frameworks for the classification of images of multiple cervical cells.
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
It has become critical to explore how machine learning and specifically deep learning methods can be exploited to analyse healthcare data.
Dual Contrastive Learning for Unsupervised Image-to-Image Translation
Unsupervised image-to-image translation tasks aim to find a mapping between a source domain X and a target domain Y from unpaired training data.
Single Underwater Image Restoration by Contrastive Learning
Underwater image restoration attracts significant attention due to its importance in unveiling the underwater world.
Mosaic Super-resolution via Sequential Feature Pyramid Networks
Additionally, to the best of our knowledge, our method is the first specialized method to super-resolve mosaic images, whether it be multi-spectral or Bayer.
Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network
This paper introduces a novel method to simultaneously super-resolve and colour-predict images acquired by snapshot mosaic sensors.
