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Found 13 papers, 4 papers with code
Medical records condensation: a roadmap towards healthcare data democratisation
The prevalence of artificial intelligence (AI) has envisioned an era of healthcare democratisation that promises every stakeholder a new and better way of life.
Self-supervised Video-centralised Transformer for Video Face Clustering
We also investigate face clustering in egocentric videos, a fast-emerging field that has not been studied yet in works related to face clustering.
Ranked #1 on
Face Clustering
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Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis for Eyewear Devices
Experimental studies with 20 participants demonstrate that, thanks to the emotionship awareness, EMOShip not only achieves superior emotion recognition accuracy over existing methods (80. 2% vs. 69. 4%), but also provides a valuable understanding of the cause of emotions.
MemX: An Attention-Aware Smart Eyewear System for Personalized Moment Auto-capture
MemX captures human visual attention on the fly, analyzes the salient visual content, and records moments of personal interest in the form of compact video snippets.
A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline
By monitoring the impact of varying resolution on the quality of high-dimensional video analytics features, hence the accuracy of video analytics results, the proposed end-to-end optimization framework learns the best non-myopic policy for dynamically controlling the resolution of input video streams to globally optimize energy efficiency.
Generalization Bound of Gradient Descent for Non-Convex Metric Learning
Metric learning aims to learn a distance measure that can benefit distance-based methods such as the nearest neighbour (NN) classifier.
Towards Certified Robustness of Distance Metric Learning
Many existing methods consider maximizing or at least constraining a distance margin in the feature space that separates similar and dissimilar pairs of instances to guarantee their generalization ability.
Dilated Convolutions with Lateral Inhibitions for Semantic Image Segmentation
Introducing LI mechanisms improves the convolutional filter's sensitivity to semantic object boundaries.
Dynamic Face Video Segmentation via Reinforcement Learning
To the best of our knowledge, this is the first work to use reinforcement learning for online key-frame decision in dynamic video segmentation, and also the first work on its application on face videos.
Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning
In contrast to this body of research, we propose to treat active learning algorithm design as a meta-learning problem and learn the best criterion from data.
Metric Learning via Maximizing the Lipschitz Margin Ratio
In this paper, we propose the Lipschitz margin ratio and a new metric learning framework for classification through maximizing the ratio.
Learning Local Metrics and Influential Regions for Classification
The performance of distance-based classifiers heavily depends on the underlying distance metric, so it is valuable to learn a suitable metric from the data.
