Search Results for author: Mohammad Mahfujur Rahman

Found 6 papers, 0 papers with code

Discriminative Domain-Invariant Adversarial Network for Deep Domain Generalization

no code implementations20 Aug 2021 Mohammad Mahfujur Rahman, Clinton Fookes, Sridha Sridharan

Domain generalization approaches aim to learn a domain invariant prediction model for unknown target domains from multiple training source domains with different distributions.

Domain Generalization

Deep Domain Generalization with Feature-norm Network

no code implementations28 Apr 2021 Mohammad Mahfujur Rahman, Clinton Fookes, Sridha Sridharan

To tackle the aforementioned problem, we introduce an end-to-end feature-norm network (FNN) which is robust to negative transfer as it does not need to match the feature distribution among the source domains.

Domain Generalization Image Classification

Preserving Semantic Consistency in Unsupervised Domain Adaptation Using Generative Adversarial Networks

no code implementations28 Apr 2021 Mohammad Mahfujur Rahman, Clinton Fookes, Sridha Sridharan

This network can achieve source to target domain matching by capturing semantic information at the feature level and producing images for unsupervised domain adaptation from both the source and the target domains.

Unsupervised Domain Adaptation

Correlation-aware Adversarial Domain Adaptation and Generalization

no code implementations29 Nov 2019 Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan

Domain adaptation (DA) and domain generalization (DG) have emerged as a solution to the domain shift problem where the distribution of the source and target data is different.

Domain Generalization

On Minimum Discrepancy Estimation for Deep Domain Adaptation

no code implementations2 Jan 2019 Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan

In the presence of large sets of labeled data, Deep Learning (DL) has accomplished extraordinary triumphs in the avenue of computer vision, particularly in object classification and recognition tasks.

Domain Adaptation General Classification +1

Multi-component Image Translation for Deep Domain Generalization

no code implementations21 Dec 2018 Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan

If DA methods are applied directly to DG by a simple exclusion of the target data from training, poor performance will result for a given task.

Domain Generalization Translation

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