67 citations · 182 across the 15 of their papers we have counts for
15 papers
Sparse Spatial Attention Network for Semantic Segmentation
Mengyu Liu, Hujun Yin
The spatial attention mechanism captures long-range dependencies by aggregating global contextual information to each query location, which is beneficial for semantic segmentation.…
Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution
Boyan Xu, Hujun Yin
Graph convolutional networks (GCNs) have achieved great success in dealing with data of non-Euclidean structures. Their success directly attributes to fitting graph structures effe…
Depth Evaluation for Metal Surface Defects by Eddy Current Testing using Deep Residual Convolutional Neural Networks
Tian Meng, Yang Tao, Ziqi Chen +10
Eddy current testing (ECT) is an effective technique in the evaluation of the depth of metal surface defects. However, in practice, the evaluation primarily relies on the experienc…
HypervolGAN: An efficient approach for GAN with multi-objective training function
Jingwen Su, Hujun Yin
Since the advent of generative adversarial networks (GANs), various loss functions have been developed and combined to constitute the overall training objective function, in order…
CNN-Based Semantic Change Detection in Satellite Imagery
Ananya Gupta, Elisabeth Welburn, Simon Watson +1
Timely disaster risk management requires accurate road maps and prompt damage assessment. Currently, this is done by volunteers manually marking satellite imagery of affected areas…
Deep Learning-based Aerial Image Segmentation with Open Data for Disaster Impact Assessment
Ananya Gupta, Simon Watson, Hujun Yin
Satellite images are an extremely valuable resource in the aftermath of natural disasters such as hurricanes and tsunamis where they can be used for risk assessment and disaster ma…
Tree Annotations in LiDAR Data Using Point Densities and Convolutional Neural Networks
Ananya Gupta, Jonathan Byrne, David Moloney +2
LiDAR provides highly accurate 3D point clouds. However, data needs to be manually labelled in order to provide subsequent useful information. Manual annotation of such data is tim…
3D Point Cloud Feature Explanations Using Gradient-Based Methods
Ananya Gupta, Simon Watson, Hujun Yin
Explainability is an important factor to drive user trust in the use of neural networks for tasks with material impact. However, most of the work done in this area focuses on image…
Multi-Temporal Aerial Image Registration Using Semantic Features
Ananya Gupta, Yao Peng, Simon Watson +1
A semantic feature extraction method for multitemporal high resolution aerial image registration is proposed in this paper. These features encode properties or information about te…
Feature Pyramid Encoding Network for Real-time Semantic Segmentation
Mengyu Liu, Hujun Yin
Although current deep learning methods have achieved impressive results for semantic segmentation, they incur high computational costs and have a huge number of parameters. For rea…
Meta-Learning with Warped Gradient Descent
Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu +3
Learning an efficient update rule from data that promotes rapid learning of new tasks from the same distribution remains an open problem in meta-learning. Typically, previous works…
Cross Attention Network for Semantic Segmentation
Mengyu Liu, Hujun Yin
In this paper, we address the semantic segmentation task with a deep network that combines contextual features and spatial information. The proposed Cross Attention Network is comp…
Breaking the Activation Function Bottleneck through Adaptive Parameterization
Sebastian Flennerhag, Hujun Yin, John Keane +1
Standard neural network architectures are non-linear only by virtue of a simple element-wise activation function, making them both brittle and excessively large. In this paper, we…
WebCaricature: a benchmark for caricature recognition
Jing Huo, Wenbin Li, Yinghuan Shi +2
Studying caricature recognition is fundamentally important to understanding of face perception. However, little research has been conducted in the computer vision community, largel…
Robust Face Recognition with Structural Binary Gradient Patterns
Weilin Huang, Hujun Yin
This paper presents a computationally efficient yet powerful binary framework for robust facial representation based on image gradients. It is termed as structural binary gradient…