71 citations · 234 across the 20 of their papers we have counts for
21 papers
Leveraging Systematic Knowledge of 2D Transformations
Jiachen Kang, Wenjing Jia, Xiangjian He
The existing deep learning models suffer from out-of-distribution (o.o.d.) performance drop in computer vision tasks. In comparison, humans have a remarkable ability to interpret i…
An Empirical Assessment of Security and Privacy Risks of Web based-Chatbots
Nazar Waheed, Muhammad Ikram, Saad Sajid Hashmi +2
Web-based chatbots provide website owners with the benefits of increased sales, immediate response to their customers, and insight into customer behaviour. While Web-based chatbots…
CAR: Class-aware Regularizations for Semantic Segmentation
Ye Huang, Di Kang, Liang Chen +4
Recent segmentation methods, such as OCR and CPNet, utilizing "class level" information in addition to pixel features, have achieved notable success for boosting the accuracy of ex…
SCADS: A Scalable Approach Using Spark in Cloud for Host-based Intrusion Detection System with System Calls
Ming Liu, Zhi Xue, Xiangjian He +1
Following the current big data trend, the scale of real-time system call traces generated by Linux applications in a contemporary data center may increase excessively. Due to the d…
What's Wrong with the Bottom-up Methods in Arbitrary-shape Scene Text Detection
Chengpei Xu, Wenjing Jia, Tingcheng Cui +3
The latest trend in the bottom-up perspective for arbitrary-shape scene text detection is to reason the links between text segments using Graph Convolutional Network (GCN). Notwith…
Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation
Ye Huang, Di Kang, Wenjing Jia +2
Spatial and channel attentions, modelling the semantic interdependencies in spatial and channel dimensions respectively, have recently been widely used for semantic segmentation. H…
EdgeLoc: An Edge-IoT Framework for Robust Indoor Localization Using Capsule Networks
Qianwen Ye, Xiaochen Fan, Gengfa Fang +4
With the unprecedented demand for location-based services in indoor scenarios, wireless indoor localization has become essential for mobile users. While GPS is not available at ind…
Binarized Graph Neural Network
Hanchen Wang, Defu Lian, Ying Zhang +4
Recently, there have been some breakthroughs in graph analysis by applying the graph neural networks (GNNs) following a neighborhood aggregation scheme, which demonstrate outstandi…
BuildSenSys: Reusing Building Sensing Data for Traffic Prediction with Cross-domain Learning
Xiaochen Fan, Chaocan Xiang, Chao Chen +5
With the rapid development of smart cities, smart buildings are generating a massive amount of building sensing data by the equipped sensors. Indeed, building sensing data provides…
Security and Privacy in IoT Using Machine Learning and Blockchain: Threats & Countermeasures
Nazar Waheed, Xiangjian He, Muhammad Ikram +2
Security and privacy of the users have become significant concerns due to the involvement of the Internet of things (IoT) devices in numerous applications. Cyber threats are growin…
PDANet: Pyramid Density-aware Attention Net for Accurate Crowd Counting
Saeed Amirgholipour, Xiangjian He, Wenjing Jia +2
Crowd counting, i.e., estimating the number of people in a crowded area, has attracted much interest in the research community. Although many attempts have been reported, crowd cou…
See More Than Once -- Kernel-Sharing Atrous Convolution for Semantic Segmentation
Ye Huang, Qingqing Wang, Wenjing Jia +1
The state-of-the-art semantic segmentation solutions usually leverage different receptive fields via multiple parallel branches to handle objects with different sizes. However, emp…
DENet: A Universal Network for Counting Crowd with Varying Densities and Scales
Lei Liu, Jie Jiang, Wenjing Jia +3
Counting people or objects with significantly varying scales and densities has attracted much interest from the research community and yet it remains an open problem. In this paper…
FACLSTM: ConvLSTM with Focused Attention for Scene Text Recognition
Qingqing Wang, Wenjing Jia, Xiangjian He +3
Scene text recognition has recently been widely treated as a sequence-to-sequence prediction problem, where traditional fully-connected-LSTM (FC-LSTM) has played a critical role. D…
Voiceprint recognition of Parkinson patients based on deep learning
Zhijing Xu, Juan Wang, Ying Zhang +1
More than 90% of the Parkinson Disease (PD) patients suffer from vocal disorders. Speech impairment is already indicator of PD. This study focuses on PD diagnosis through voiceprin…
A-CCNN: adaptive ccnn for density estimation and crowd counting
Saeed Amirgholipour Kasmani, Xiangjian He, Wenjing Jia +2
Crowd counting, for estimating the number of people in a crowd using vision-based computer techniques, has attracted much interest in the research community. Although many attempts…
Beyond Context: Exploring Semantic Similarity for Tiny Face Detection
Yue Xi, Jiangbin Zheng, Xiangjian He +2
Tiny face detection aims to find faces with high degrees of variability in scale, resolution and occlusion in cluttered scenes. Due to the very little information available on tiny…
A Structural Correlation Filter Combined with A Multi-task Gaussian Particle Filter for Visual Tracking
Manna Dai, Shuying Cheng, Xiangjian He +1
In this paper, we propose a novel structural correlation filter combined with a multi-task Gaussian particle filter (KCF-GPF) model for robust visual tracking. We first present an…
Structured Inhomogeneous Density Map Learning for Crowd Counting
Hanhui Li, Xiangjian He, Hefeng Wu +4
In this paper, we aim at tackling the problem of crowd counting in extremely high-density scenes, which contain hundreds, or even thousands of people. We begin by a comprehensive a…
Soft Locality Preserving Map (SLPM) for Facial Expression Recognition
Cigdem Turan, Kin-Man Lam, Xiangjian He
For image recognition, an extensive number of methods have been proposed to overcome the high-dimensionality problem of feature vectors being used. These methods vary from unsuperv…
Face Parsing via a Fully-Convolutional Continuous CRF Neural Network
Lei Zhou, Zhi Liu, Xiangjian He
In this work, we address the face parsing task with a Fully-Convolutional continuous CRF Neural Network (FC-CNN) architecture. In contrast to previous face parsing methods that app…