Monash University

research

∙ 09/11/2019

InceptionTime: Finding AlexNet for Time Series Classification

Time series classification (TSC) is the area of machine learning interes...

Hassan Ismail Fawaz, et al. ∙

research

∙ 04/23/2022

Smart App Attack: Hacking Deep Learning Models in Android Apps

On-device deep learning is rapidly gaining popularity in mobile applicat...

Yujin Huang, et al. ∙

research

∙ 01/24/2022

Multi-Graph Fusion Networks for Urban Region Embedding

Learning the embeddings for urban regions from human mobility data can r...

Shangbin Wu, et al. ∙

research

∙ 05/25/2020

A Bayesian-inspired, deep learning, semi-supervised domain adaptation technique for land cover mapping

Land cover maps are a vital input variable to many types of environmenta...

Benjamin Lucas, et al. ∙

research

∙ 12/23/2019

Low radiation tomographic reconstruction with and without template information

Low-dose tomography is highly preferred in medical procedures for its re...

Preeti Gopal, et al. ∙

research

∙ 06/03/2020

Hierarchical forecast reconciliation with machine learning

Hierarchical forecasting methods have been widely used to support aligne...

Evangelos Spiliotis, et al. ∙

research

∙ 07/30/2021

Creating Powerful and Interpretable Models withRegression Networks

As the discipline has evolved, research in machine learning has been foc...

Lachlan O'Neill, et al. ∙

research

∙ 01/19/2022

Dual Space Graph Contrastive Learning

Unsupervised graph representation learning has emerged as a powerful too...

Haoran Yang, et al. ∙

research

∙ 08/04/2021

Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization

Retinal vessel segmentation plays a key role in computer-aided screening...

Wei Feng, et al. ∙

research

∙ 10/03/2019

Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions

Deep neural network image classifiers are reported to be susceptible to ...

He Zhao, et al. ∙

research

∙ 11/29/2019

Blockwisely Supervised Neural Architecture Search with Knowledge Distillation

Neural Architecture Search (NAS), aiming at automatically designing netw...

Changlin Li, et al. ∙

research

∙ 04/13/2020

Speak2Label: Using Domain Knowledge for Creating a Large Scale Driver Gaze Zone Estimation Dataset

Labelling of human behavior analysis data is a complex and time consumin...

Shreya Ghosh, et al. ∙

research

∙ 05/08/2020

Active Preference Learning using Maximum Regret

We study active preference learning as a framework for intuitively speci...

Nils Wilde, et al. ∙

research

∙ 07/27/2021

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification

Brain functional connectivity (FC) reveals biomarkers for identification...

Fuad Noman, et al. ∙

research

∙ 09/21/2021

Enforcing Mutual Consistency of Hard Regions for Semi-supervised Medical Image Segmentation

In this paper, we proposed a novel mutual consistency network (MC-Net+) ...

Yicheng Wu, et al. ∙

research

∙ 09/10/2019

LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns

Generating forecasts for time series with multiple seasonal cycles is an...

Kasun Bandara, et al. ∙

research

∙ 01/06/2020

Generating Semantic Adversarial Examples via Feature Manipulation

The vulnerability of deep neural networks to adversarial attacks has bee...

Shuo Wang, et al. ∙

research

∙ 02/11/2020

Learning Coupled Policies for Simultaneous Machine Translation

In simultaneous machine translation, the system needs to incrementally g...

Philip Arthur, et al. ∙

research

∙ 07/07/2021

Growing and Evolving 3D Prints

Design - especially of physical objects - can be understood as creative ...

Jon McCormack, et al. ∙

research

∙ 08/19/2021

Exploiting Scene Graphs for Human-Object Interaction Detection

Human-Object Interaction (HOI) detection is a fundamental visual task ai...

Tao He, et al. ∙

research

∙ 07/29/2022

SERCNN: Stacked Embedding Recurrent Convolutional Neural Network in Detecting Depression on Twitter

Conventional approaches to identify depression are not scalable, and the...

Heng Ee Tay, et al. ∙

research

∙ 04/22/2021

Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition

In the real world, medical datasets often exhibit a long-tailed data dis...

Lie Ju, et al. ∙

research

∙ 02/02/2020

A Survey on Knowledge Graphs: Representation, Acquisition and Applications

Human knowledge provides a formal understanding of the world. Knowledge ...

Shaoxiong Ji, et al. ∙

research

∙ 01/18/2020

OIAD: One-for-all Image Anomaly Detection with Disentanglement Learning

Anomaly detection aims to recognize samples with anomalous and unusual p...

Shuo Wang, et al. ∙

research

∙ 03/12/2020

ZSTAD: Zero-Shot Temporal Activity Detection

An integral part of video analysis and surveillance is temporal activity...

Lingling Zhang, et al. ∙

research

∙ 06/04/2022

Nerfels: Renderable Neural Codes for Improved Camera Pose Estimation

This paper presents a framework that combines traditional keypoint-based...

Gil Avraham, et al. ∙

research

∙ 05/08/2020

Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks

Influence maximization is a widely studied topic in network science, whe...

Moein Khajehnejad, et al. ∙

research

∙ 05/29/2020

Not made for each other- Audio-Visual Dissonance-based Deepfake Detection and Localization

We propose detection of deepfake videos based on the dissimilarity betwe...

Komal Chugh, et al. ∙

research

∙ 08/22/2021

Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training Consistency Shift

Recently proposed neural architecture search (NAS) methods co-train bill...

Jiefeng Peng, et al. ∙

research

∙ 01/05/2022

Complexity and Aesthetics in Generative and Evolutionary Art

In this paper we examine the concept of complexity as it applies to gene...

Jon McCormack, et al. ∙

research

∙ 03/18/2020

OpenGAN: Open Set Generative Adversarial Networks

Many existing conditional Generative Adversarial Networks (cGANs) are li...

Luke Ditria, et al. ∙

research

∙ 09/29/2021

Real-Time Multi-Level Neonatal Heart and Lung Sound Quality Assessment for Telehealth Applications

Digital stethoscopes in combination with telehealth allow chest sounds t...

Ethan Grooby, et al. ∙

research

∙ 11/19/2021

Medical Visual Question Answering: A Survey

Medical Visual Question Answering (VQA) is a combination of medical arti...

Zhihong Lin, et al. ∙

research

∙ 11/25/2021

Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting

Recent studies focus on formulating the traffic forecasting as a spatio-...

Chuanpan Zheng, et al. ∙

research

∙ 02/14/2022

Graph Neural Networks for Graphs with Heterophily: A Survey

Recent years have witnessed fast developments of graph neural networks (...

Xin Zheng, et al. ∙

research

∙ 03/21/2022

Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields

Image translation and manipulation have gain increasing attention along ...

Yuedong Chen, et al. ∙

research

∙ 03/28/2022

Automated Progressive Learning for Efficient Training of Vision Transformers

Recent advances in vision Transformers (ViTs) have come with a voracious...

Changlin Li, et al. ∙

research

∙ 04/15/2020

Understanding Aesthetic Evaluation using Deep Learning

A bottleneck in any evolutionary art system is aesthetic evaluation. Man...

Jon McCormack, et al. ∙

research

∙ 12/17/2021

Challenge Dataset of Cognates and False Friend Pairs from Indian Languages

Cognates are present in multiple variants of the same text across differ...

Diptesh Kanojia, et al. ∙

research

∙ 01/11/2022

Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task

This paper proposes an adversarial learning based training approach for ...

Himashi Peiris, 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

∙ 06/06/2020

Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report Generation

Beyond the common difficulties faced in the natural image captioning, me...

Mingjie Li, et al. ∙

research

∙ 05/02/2021

Learning data association without data association: An EM approach to neural assignment prediction

Data association is a fundamental component of effective multi-object tr...

Michael Burke, et al. ∙

research

∙ 07/09/2021

GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network

Deep Neural Networks (DNN) are known to be vulnerable to adversarial sam...

Zuohui Chen, et al. ∙

research

∙ 06/03/2022

Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination

Graph contrastive learning (GCL) alleviates the heavy reliance on label ...

Yizhen Zheng, et al. ∙

research

∙ 08/11/2019

LoRMIkA: Local Rule-based Model Interpretability with k-optimal Associations

As we rely more and more on machine learning models for real-life decisi...

Dilini Rajapaksha, et al. ∙

research

∙ 03/30/2020

Real-time Fruit Recognition and Grasp Estimation for Autonomous Apple harvesting

In this research, a fully neural network based visual perception framewo...

Hanwen Kang, et al. ∙

research

∙ 07/10/2020

Improving Adversarial Robustness by Enforcing Local and Global Compactness

The fact that deep neural networks are susceptible to crafted perturbati...

Anh Bui, et al. ∙

research

∙ 01/18/2021

DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection

Deep learning models are increasingly used in mobile applications as cri...

Yuanchun Li, et al. ∙

research

∙ 07/27/2021

Remember What You have drawn: Semantic Image Manipulation with Memory

Image manipulation with natural language, which aims to manipulate image...

Xiangxi Shi, et al. ∙

Monash University

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