Dependable modulation classifier explainer with measurable explainability [0.03%]
具备可测量解释性的可靠调制分类器解释模型
Gaurav Duggal,Tejas Gaikwad,Bhupendra Sinha
Gaurav Duggal
The Internet of Things (IoT) plays a significant role in building smart cities worldwide. Smart cities use IoT devices to collect and analyze data to provide better services and solutions. These IoT devices are heavily dependent on the netw...
ProKnow: Process knowledge for safety constrained and explainable question generation for mental health diagnostic assistance [0.03%]
基于过程知识的安全约束和可解释的问题生成用于心理健康诊断辅助
Kaushik Roy,Manas Gaur,Misagh Soltani et al.
Kaushik Roy et al.
Virtual Mental Health Assistants (VMHAs) are utilized in health care to provide patient services such as counseling and suggestive care. They are not used for patient diagnostic assistance because they cannot adhere to safety constraints an...
From video summarization to real time video summarization in smart cities and beyond: A survey [0.03%]
从视频概要到实时视频概要在智慧城市及其他领域中的应用：一项调查研究
Prashant Giridhar Shambharkar,Ruchi Goel
Prashant Giridhar Shambharkar
With the massive expansion of videos on the internet, searching through millions of them has become quite challenging. Smartphones, recording devices, and file sharing are all examples of ways to capture massive amounts of real time video. ...
Socio-technical system analysis of responsible data sharing in water systems as critical infrastructure [0.03%]
水系统作为关键基础设施的责任数据共享的社会技术系统分析
Peter Hazell,Peter Novitzky,Steven van den Oord
Peter Hazell
Attention is increasingly focused on the protection of water systems as critical infrastructure, including subsystems of supply, sanitation, hygiene, and management. Similarly increasing consideration is paid to the growing role and impact ...
Fair classification via domain adaptation: A dual adversarial learning approach [0.03%]
通过领域适应实现公平分类：一种双重对抗学习方法
Yueqing Liang,Canyu Chen,Tian Tian et al.
Yueqing Liang et al.
Modern machine learning (ML) models are becoming increasingly popular and are widely used in decision-making systems. However, studies have shown critical issues of ML discrimination and unfairness, which hinder their adoption on high-stake...
Xiyao Fu,Zhexian Sun,Haoteng Tang et al.
Xiyao Fu et al.
As one of the popular deep learning methods, deep convolutional neural networks (DCNNs) have been widely adopted in segmentation tasks and have received positive feedback. However, in segmentation tasks, DCNN-based frameworks are known for ...
The effects of long COVID-19, its severity, and the need for immediate attention: Analysis of clinical trials and Twitter data [0.03%]
长新冠的影响，其严重性以及需要立即关注的需求：临床试验和推特数据分析
Arinjita Bhattacharyya,Anand Seth,Shesh Rai
Arinjita Bhattacharyya
Background: The coronavirus disease 2019 (COVID-19) has been declared a pandemic since March 2020 by the World Health Organization; identifying the disease progression, predicting patient outcomes early, the possibility o...
Rubayet Bin Mostafiz,Md Adilur Rahim,Carol J Friedland et al.
Rubayet Bin Mostafiz et al.
Model output of localized flood grids are useful in characterizing flood hazards for properties located in the Special Flood Hazard Area (SFHA-areas expected to experience a 1% or greater annual chance of flooding). However, due to the unav...
Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis [0.03%]
生活方式对全球痴呆症发病率影响的解释性人工智能分析
Loredana Bellantuono,Alfonso Monaco,Nicola Amoroso et al.
Loredana Bellantuono et al.
Introduction: Dementia is an umbrella term indicating a group of diseases that affect the cognitive sphere. Dementia is not a mere individual health issue, since its interference with the ability to carry out daily activi...
Patrick Taylor Smith
Patrick Taylor Smith
This paper offers a novel understanding of collective responsibility for AI outcomes that can help resolve the "problem of many hands" and "responsibility gaps" when it comes to AI failure, especially in the context of lethal autonomous wea...