activity
20182022
most citedAdversarial Network with Multiple Classifiers for Open Set Domain Adaptation

103 citations · 118 across the 7 of their papers we have counts for

collaborators

11 papers

cs.CV2022

A Guide to Employ Hyperspectral Imaging for Assessing Wheat Quality at Different Stages of Supply Chain in Australia: A Review

Priyabrata Karmakar, Shyh Wei Teng. Manzur Murshed, Paul Pang +1

Wheat is one of the major staple crops across the globe. Therefore, it is mandatory to measure, maintain and improve the wheat quality for human consumption. Traditional wheat qual…

cs.CV20214 cited

Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring and Activation Function

Md Tahmid Hossain, Shyh Wei Teng, Ferdous Sohel +1

Deep convolutional networks are vulnerable to image translation or shift, partly due to common down-sampling layers, e.g., max-pooling and strided convolution. These operations vio…

cs.CV2021

A novel network training approach for open set image recognition

Md Tahmid Hossain, Shyh Wei Teng, Guojun Lu +1

Convolutional Neural Networks (CNNs) are commonly designed for closed set arrangements, where test instances only belong to some "Known Known" (KK) classes used in training. As suc…

cs.SI2021

Network Representation Learning: From Traditional Feature Learning to Deep Learning

Ke Sun, Lei Wang, Bo Xu +3

Network representation learning (NRL) is an effective graph analytics technique and promotes users to deeply understand the hidden characteristics of graph data. It has been succes…

cs.SD202111 cited

Thank you for Attention: A survey on Attention-based Artificial Neural Networks for Automatic Speech Recognition

Priyabrata Karmakar, Shyh Wei Teng, Guojun Lu

Attention is a very popular and effective mechanism in artificial neural network-based sequence-to-sequence models. In this survey paper, a comprehensive review of the different at…

cs.CV2021

Integrated Generalized Zero-Shot Learning for Fine-Grained Classification

Tasfia Shermin, Shyh Wei Teng, Ferdous Sohel +2

Embedding learning (EL) and feature synthesizing (FS) are two of the popular categories of fine-grained GZSL methods. EL or FS using global features cannot discriminate fine detail…