Deakin University

research

∙ 04/23/2021

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

Face deepfake detection has seen impressive results recently. Nearly all...

Sheldon Fung, et al. ∙

research

∙ 02/11/2019

Improving Generalization and Stability of Generative Adversarial Networks

Generative Adversarial Networks (GANs) are one of the most popular tools...

Hoang Thanh-Tung, et al. ∙

research

∙ 02/27/2020

Review, Analyze, and Design a Comprehensive Deep Reinforcement Learning Framework

Reinforcement learning (RL) has emerged as a standard approach for build...

Ngoc Duy Nguyen, et al. ∙

research

∙ 01/19/2020

Distributionally Robust Bayesian Quadrature Optimization

Bayesian quadrature optimization (BQO) maximizes the expectation of an e...

Thanh Tang Nguyen, et al. ∙

research

∙ 08/08/2021

Self-Adversarial Disentangling for Specific Domain Adaptation

Domain adaptation aims to bridge the domain shifts between the source an...

Qianyu Zhou, et al. ∙

research

∙ 04/11/2022

Dependable Intrusion Detection System for IoT: A Deep Transfer Learning-based Approach

Security concerns for IoT applications have been alarming because of the...

Sk. Tanzir Mehedi, et al. ∙

research

∙ 07/24/2021

An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products

Defects are unavoidable in casting production owing to the complexity of...

Maryam Habibpour, et al. ∙

research

∙ 05/22/2020

Spoof Face Detection Via Semi-Supervised Adversarial Training

Face spoofing causes severe security threats in face recognition systems...

Chengwei Chen, et al. ∙

research

∙ 10/20/2021

Deep Point Cloud Normal Estimation via Triplet Learning

Normal estimation on 3D point clouds is a fundamental problem in 3D visi...

Weijia Wang, et al. ∙

research

∙ 01/18/2021

What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space

Deep neural networks (DNNs) have been widely adopted in different applic...

Shihao Zhao, et al. ∙

research

∙ 03/10/2022

A Systematic Literature Review on Blockchain Enabled Federated Learning Framework for Internet of Vehicles

While the convergence of Artificial Intelligence (AI) techniques with im...

Mustain Billah, et al. ∙

research

∙ 02/10/2020

Self-Assttentive Associative Memory

Heretofore, neural networks with external memory are restricted to singl...

Hung Le, et al. ∙

research

∙ 12/03/2021

Episodic Policy Gradient Training

We introduce a novel training procedure for policy gradient methods wher...

Hung Le, et al. ∙

research

∙ 02/10/2020

Self-Attentive Associative Memory

Heretofore, neural networks with external memory are restricted to singl...

Hung Le, et al. ∙

research

∙ 08/24/2021

MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification

Breast histology image classification is a crucial step in the early dia...

Zakaria Senousy, et al. ∙

research

∙ 11/03/2021

Model-Based Episodic Memory Induces Dynamic Hybrid Controls

Episodic control enables sample efficiency in reinforcement learning by ...

Hung Le, et al. ∙

research

∙ 10/18/2020

Hierarchical Conditional Relation Networks for Multimodal Video Question Answering

Video QA challenges modelers in multiple fronts. Modeling video necessit...

Thao Minh Le, et al. ∙

research

∙ 05/27/2020

Interpretable and Efficient Heterogeneous Graph Convolutional Network

Graph Convolutional Network (GCN) has achieved extraordinary success in ...

Yaming Yang, et al. ∙

research

∙ 06/24/2018

SSIMLayer: Towards Robust Deep Representation Learning via Nonlinear Structural Similarity

Deeper convolutional neural networks provide more capacity to approximat...

Ahmed Abobakr, et al. ∙

research

∙ 09/19/2018

Bayesian functional optimisation with shape prior

Real world experiments are expensive, and thus it is important to reach ...

Pratibha Vellanki, et al. ∙

research

∙ 12/27/2018

Towards effective AI-powered agile project management

The rise of Artificial intelligence (AI) has the potential to significan...

Hoa Khanh Dam, et al. ∙

research

∙ 04/01/2019

PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study

This paper introduces a newly collected and novel dataset (StereoMSI) fo...

Mehrdad Shoeiby, et al. ∙

research

∙ 08/26/2019

Theory and Evaluation Metrics for Learning Disentangled Representations

We make two theoretical contributions to disentanglement learning by (a)...

Kien Do, et al. ∙

research

∙ 07/05/2020

Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks

Recent studies have shown that DNNs can be compromised by backdoor attac...

Yunfei Liu, et al. ∙

research

∙ 09/05/2019

Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network

This paper introduces a novel method to simultaneously super-resolve and...

Mehrdad Shoeiby, et al. ∙

research

∙ 10/07/2021

Learning post-processing for QRS detection using Recurrent Neural Network

Deep-learning based QRS-detection algorithms often require essential pos...

Ahsan Habib, et al. ∙

research

∙ 03/08/2019

Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos

Appearance features have been widely used in video anomaly detection eve...

Romero Morais, et al. ∙

research

∙ 09/06/2019

Explicit Facial Expression Transfer via Fine-Grained Semantic Representations

Facial expression transfer between two unpaired images is a challenging ...

Zhiwen Shao, et al. ∙

research

∙ 02/27/2020

A Visual Communication Map for Multi-Agent Deep Reinforcement Learning

Multi-agent learning distinctly poses significant challenges in the effo...

Ngoc Duy Nguyen, et al. ∙

research

∙ 07/24/2021

Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support

We address policy learning with logged data in contextual bandits. Curre...

Hung Tran-The, et al. ∙

research

∙ 01/05/2019

Learning to Remember More with Less Memorization

Memory-augmented neural networks consisting of a neural controller and a...

Hung Le, et al. ∙

research

∙ 03/26/2019

Kernel-Free Image Deblurring with a Pair of Blurred/Noisy Images

Complex blur like the mixup of space-variant and space-invariant blur, w...

Chunzhi Gu, et al. ∙

research

∙ 07/10/2019

Learning to Reason with Relational Video Representation for Question Answering

How does machine learn to reason about the content of a video in answeri...

Thao Minh Le, et al. ∙

research

∙ 02/26/2020

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling

Scientific experiments are usually expensive due to complex experimental...

Cheng Li, et al. ∙

research

∙ 12/19/2021

Improving Face-Based Age Estimation with Attention-Based Dynamic Patch Fusion

With the increasing popularity of convolutional neural networks (CNNs), ...

Haoyi Wang, et al. ∙

research

∙ 03/26/2022

SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks

Federated learning (FL) is a key enabler for efficient communication and...

Won Joon Yun, et al. ∙

research

∙ 04/05/2022

Attention Distraction: Watermark Removal Through Continual Learning with Selective Forgetting

Fine-tuning attacks are effective in removing the embedded watermarks in...

Qi Zhong, et al. ∙

research

∙ 03/27/2020

Incorporating Expert Prior in Bayesian Optimisation via Space Warping

Bayesian optimisation is a well-known sample-efficient method for the op...

Anil Ramachandran, et al. ∙

research

∙ 07/26/2020

An Uncertainty-aware Transfer Learning-based Framework for Covid-19 Diagnosis

The early and reliable detection of COVID-19 infected patients is essent...

Afshar Shamsi Jokandan, et al. ∙

research

∙ 04/20/2022

Memory-Constrained Policy Optimization

We introduce a new constrained optimization method for policy gradient r...

Hung Le, et al. ∙

research

∙ 06/12/2018

Multi-Agent Deep Reinforcement Learning with Human Strategies

Deep learning has enabled traditional reinforcement learning methods to ...

Thanh Nguyen, et al. ∙

research

∙ 07/11/2018

On catastrophic forgetting and mode collapse in Generative Adversarial Networks

Generative Adversarial Networks (GAN) are one of the most prominent tool...

Hoang Thanh-Tung, et al. ∙

research

∙ 04/22/2020

Warwick Image Forensics Dataset for Device Fingerprinting In Multimedia Forensics

Device fingerprints like sensor pattern noise (SPN) are widely used for ...

Yijun Quan, et al. ∙

research

∙ 07/01/2020

Age-Oriented Face Synthesis with Conditional Discriminator Pool and Adversarial Triplet Loss

The vanilla Generative Adversarial Networks (GAN) are commonly used to g...

Haoyi Wang, et al. ∙

research

∙ 03/22/2020

HDF: Hybrid Deep Features for Scene Image Representation

Nowadays it is prevalent to take features extracted from pre-trained dee...

Chiranjibi Sitaula, et al. ∙

research

∙ 04/04/2020

Attacking with bitcoin: Using Bitcoin to Build Resilient Botnet Armies

We focus on the problem of botnet orchestration and discuss how attacker...

Dimitri Kamenski, et al. ∙

research

∙ 06/24/2020

Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness

Evaluating the robustness of a defense model is a challenging task in ad...

Linxi Jiang, et al. ∙

research

∙ 04/12/2021

Object-Centric Representation Learning for Video Question Answering

Video question answering (Video QA) presents a powerful testbed for huma...

Long Hoang Dang, et al. ∙

research

∙ 08/08/2017

Automatic feature learning for vulnerability prediction

Code flaws or vulnerabilities are prevalent in software systems and can ...

Hoa Khanh Dam, et al. ∙

research

∙ 11/06/2017

KGAN: How to Break The Minimax Game in GAN

Generative Adversarial Networks (GANs) were intuitively and attractively...

Trung Le, et al. ∙

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