activity
20192021
most citedAdversarial Network with Multiple Classifiers for Open Set Domain Adaptation

103 citations · 106 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2021

A Survey of Deep Learning Techniques for Weed Detection from Images

A S M Mahmudul Hasan, Ferdous Sohel, Dean Diepeveen +2

The rapid advances in Deep Learning (DL) techniques have enabled rapid detection, localisation, and recognition of objects from images or videos. DL techniques are now being used i…

cs.CV2020

Bidirectional Mapping Coupled GAN for Generalized Zero-Shot Learning

Tasfia Shermin, Shyh Wei Teng, Ferdous Sohel +2

Bidirectional mapping-based generalized zero-shot learning (GZSL) methods rely on the quality of synthesized features to recognize seen and unseen data. Therefore, learning a joint…

cs.LG2020

Imputation of Missing Data with Class Imbalance using Conditional Generative Adversarial Networks

Saqib Ejaz Awan, Mohammed Bennamoun, Ferdous Sohel +2

Missing data is a common problem faced with real-world datasets. Imputation is a widely used technique to estimate the missing data. State-of-the-art imputation approaches, such as…

eess.IV20202 cited

RCNN for Region of Interest Detection in Whole Slide Images

A Nugaliyadde, Kok Wai Wong, Jeremy Parry +5

Digital pathology has attracted significant attention in recent years. Analysis of Whole Slide Images (WSIs) is challenging because they are very large, i.e., of Giga-pixel resolut…

cs.CV2020103 cited

Adversarial Network with Multiple Classifiers for Open Set Domain Adaptation

Tasfia Shermin, Guojun Lu, Shyh Wei Teng +2

Domain adaptation aims to transfer knowledge from a domain with adequate labeled samples to a domain with scarce labeled samples. Prior research has introduced various open set dom…

cs.CV2020

Unconstrained Matching of 2D and 3D Descriptors for 6-DOF Pose Estimation

Uzair Nadeem, Mohammed Bennamoun, Roberto Togneri +1

This paper proposes a novel concept to directly match feature descriptors extracted from 2D images with feature descriptors extracted from 3D point clouds. We use this concept to d…