56 citations · 134 across the 12 of their papers we have counts for
12 papers
Medical records condensation: a roadmap towards healthcare data democratisation
Yujiang Wang, Anshul Thakur, Mingzhi Dong +5
The prevalence of artificial intelligence (AI) has envisioned an era of healthcare democratisation that promises every stakeholder a new and better way of life. However, the advanc…
Self-supervised Video-centralised Transformer for Video Face Clustering
Yujiang Wang, Mingzhi Dong, Jie Shen +5
This paper presents a novel method for face clustering in videos using a video-centralised transformer. Previous works often employed contrastive learning to learn frame-level repr…
Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis for Eyewear Devices
Yingying Zhao, Yuhu Chang, Yutian Lu +8
Emotion recognition in smart eyewear devices is highly valuable but challenging. One key limitation of previous works is that the expression-related information like facial or eye…
A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline
Yingying Zhao, Mingzhi Dong, Yujiang Wang +7
Deep-learning-based video processing has yielded transformative results in recent years. However, the video analytics pipeline is energy-intensive due to high data rates and relian…
MemX: An Attention-Aware Smart Eyewear System for Personalized Moment Auto-capture
Yuhu Chang, Yingying Zhao, Mingzhi Dong +7
This work presents MemX: a biologically-inspired attention-aware eyewear system developed with the goal of pursuing the long-awaited vision of a personalized visual Memex. MemX cap…
Towards Certified Robustness of Distance Metric Learning
Xiaochen Yang, Yiwen Guo, Mingzhi Dong +1
Metric learning aims to learn a distance metric such that semantically similar instances are pulled together while dissimilar instances are pushed away. Many existing methods consi…
Dilated Convolutions with Lateral Inhibitions for Semantic Image Segmentation
Yujiang Wang, Mingzhi Dong, Jie Shen +2
Dilated convolutions are widely used in deep semantic segmentation models as they can enlarge the filters' receptive field without adding additional weights nor sacrificing spatial…
Dynamic Face Video Segmentation via Reinforcement Learning
Yujiang Wang, Mingzhi Dong, Jie Shen +3
For real-time semantic video segmentation, most recent works utilised a dynamic framework with a key scheduler to make online key/non-key decisions. Some works used a fixed key sch…
Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice
Kunkun Pang, Mingzhi Dong, Yang Wu +1
Active learning aims to reduce annotation cost by predicting which samples are useful for a human teacher to label. However it has become clear there is no best active learning alg…
Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning
Kunkun Pang, Mingzhi Dong, Yang Wu +1
Active learning (AL) aims to enable training high performance classifiers with low annotation cost by predicting which subset of unlabelled instances would be most beneficial to la…
Metric Learning via Maximizing the Lipschitz Margin Ratio
Mingzhi Dong, Xiaochen Yang, Yang Wu +1
In this paper, we propose the Lipschitz margin ratio and a new metric learning framework for classification through maximizing the ratio. This framework enables the integration of…
Learning Local Metrics and Influential Regions for Classification
Mingzhi Dong, Yujiang Wang, Xiaochen Yang +1
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. To address the problem…