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20182025
most citedAdversarial Network with Multiple Classifiers for Open Set Domain Adaptation

103 citations · 118 across the 10 of their papers we have counts for

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11 papers · 1 filter

cs.CV2025

Evaluating the Efficacy of Sentinel-2 versus Aerial Imagery in Serrated Tussock Classification

Rezwana Sultana, Manzur Murshed, Kathryn Sheffield +3

Invasive species pose major global threats to ecosystems and agriculture. Serrated tussock (\textit{Nassella trichotoma}) is a highly competitive invasive grass species that disrup…

cs.CV2024

Hyperspectral Imaging-Based Grain Quality Assessment With Limited Labelled Data

Priyabrata Karmakar, Manzur Murshed, Shyh Wei Teng

Recently hyperspectral imaging (HSI)-based grain quality assessment has gained research attention. However, unlike other imaging modalities, HSI data lacks sufficient labelled samp…

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.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…