97 citations · 196 across the 22 of their papers we have counts for
23 papers
Designing Automation Boundaries for Trustworthy Smart Medication Support
Liqian You, Jianlong Zhou
Smart medication systems increasingly automate medication recognition, reminders, and logging. However, automation in home medication routines should be carefully bounded, as users…
A Survey of TinyML Applications in Beekeeping for Hive Monitoring and Management
Willy Sucipto, Jianlong Zhou, Ray Seung Min Kwon +1
Honey bee colonies are essential for global food security and ecosystem stability, yet they face escalating threats from pests, diseases, and environmental stressors. Traditional h…
ABE: A Unified Framework for Robust and Faithful Attribution-Based Explainability
Zhiyu Zhu, Jiayu Zhang, Zhibo Jin +2
Attribution algorithms are essential for enhancing the interpretability and trustworthiness of deep learning models by identifying key features driving model decisions. Existing fr…
Can LLM Assist in the Evaluation of the Quality of Machine Learning Explanations?
Bo Wang, Yiqiao Li, Jianlong Zhou +1
EXplainable machine learning (XML) has recently emerged to address the mystery mechanisms of machine learning (ML) systems by interpreting their 'black box' results. Despite the de…
Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability
Zhiyu Zhu, Zhibo Jin, Jiayu Zhang +4
The task of identifying multimodal image-text representations has garnered increasing attention, particularly with models such as CLIP (Contrastive Language-Image Pretraining), whi…
E-LENS: User Requirements-Oriented AI Ethics Assurance
Jianlong Zhou, Fang Chen
Despite the much proliferation of AI ethical principles in recent years, there is a challenge of assuring AI ethics with current AI ethics frameworks in real-world applications. Wh…
Attribution for Enhanced Explanation with Transferable Adversarial eXploration
Zhiyu Zhu, Jiayu Zhang, Zhibo Jin +3
The interpretability of deep neural networks is crucial for understanding model decisions in various applications, including computer vision. AttEXplore++, an advanced framework bu…
AI Ethics in Smart Homes: Progress, User Requirements and Challenges
Liqian You, Jianlong Zhou, Zhiwei Li +1
With the rise of Internet of Things (IoT) technologies in smart homes and the integration of artificial intelligence (AI), ethical concerns have become increasingly significant. Th…
Enhancing Transferability of Adversarial Attacks with GE-AdvGAN+: A Comprehensive Framework for Gradient Editing
Zhibo Jin, Jiayu Zhang, Zhiyu Zhu +4
Transferable adversarial attacks pose significant threats to deep neural networks, particularly in black-box scenarios where internal model information is inaccessible. Studying ad…
Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack
Zhibo Jin, Jiayu Zhang, Zhiyu Zhu +4
In recent times, the swift evolution of adversarial attacks has captured widespread attention, particularly concerning their transferability and other performance attributes. These…
Interpretable Robotic Manipulation from Language
Boyuan Zheng, Jianlong Zhou, Fang Chen
Humans naturally employ linguistic instructions to convey knowledge, a process that proves significantly more complex for machines, especially within the context of multitask robot…
ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks
Yiqiao Li, Jianlong Zhou, Yifei Dong +2
Graph neural networks (GNNs) have proven their efficacy in a variety of real-world applications, but their underlying mechanisms remain a mystery. To address this challenge and ena…
Full-resolution Lung Nodule Segmentation from Chest X-ray Images using Residual Encoder-Decoder Networks
Michael James Horry, Subrata Chakraborty, Biswajeet Pradhan +6
Lung cancer is the leading cause of cancer death and early diagnosis is associated with a positive prognosis. Chest X-ray (CXR) provides an inexpensive imaging mode for lung cancer…
Ethical ChatGPT: Concerns, Challenges, and Commandments
Jianlong Zhou, Heimo Müller, Andreas Holzinger +1
Large language models, e.g. ChatGPT are currently contributing enormously to make artificial intelligence even more popular, especially among the general population. However, such…
Genetic Imitation Learning by Reward Extrapolation
Boyuan Zheng, Jianlong Zhou, Fang Chen
Imitation learning demonstrates remarkable performance in various domains. However, imitation learning is also constrained by many prerequisites. The research community has done in…
Explaining Imitation Learning through Frames
Boyuan Zheng, Jianlong Zhou, Chunjie Liu +2
As one of the prevalent methods to achieve automation systems, Imitation Learning (IL) presents a promising performance in a wide range of domains. However, despite the considerabl…
GANExplainer: GAN-based Graph Neural Networks Explainer
Yiqiao Li, Jianlong Zhou, Boyuan Zheng +1
With the rapid deployment of graph neural networks (GNNs) based techniques into a wide range of applications such as link prediction, node classification, and graph classification…
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics
Yiqiao Li, Jianlong Zhou, Sunny Verma +1
Graph neural networks (GNNs) have demonstrated a significant boost in prediction performance on graph data. At the same time, the predictions made by these models are often hard to…
Understanding Relations Between Perception of Fairness and Trust in Algorithmic Decision Making
Jianlong Zhou, Sunny Verma, Mudit Mittal +1
Algorithmic processes are increasingly employed to perform managerial decision making, especially after the tremendous success in Artificial Intelligence (AI). This paradigm shift…
Imitation Learning: Progress, Taxonomies and Challenges
Boyuan Zheng, Sunny Verma, Jianlong Zhou +2
Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors. Its success has been demonstra…
Facilitating Machine Learning Model Comparison and Explanation Through A Radial Visualisation
Jianlong Zhou, Weidong Huang, Fang Chen
Building an effective Machine Learning (ML) model for a data set is a difficult task involving various steps. One of the most important steps is to compare generated substantial am…
Detecting Community Depression Dynamics Due to COVID-19 Pandemic in Australia
Jianlong Zhou, Hamad Zogan, Shuiqiao Yang +3
The recent COVID-19 pandemic has caused unprecedented impact across the globe. We have also witnessed millions of people with increased mental health issues, such as depression, st…
Examination of Community Sentiment Dynamics due to COVID-19 Pandemic: A Case Study from A State in Australia
Jianlong Zhou, Shuiqiao Yang, Chun Xiao +1
The outbreak of the novel Coronavirus Disease 2019 (COVID-19) has caused unprecedented impacts to people's daily life around the world. Various measures and policies such as lockdo…