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Machine Learning (ML) models have the potential to support decision-making in healthcare by grasping complex patterns within data. However, decisions in this domain are sensitive and require active involvement of domain specialists with deep knowledge of ...

Graph neural networks (GNNs) have become a popular approach for semi-supervised graph representation learning. GNNs research has generally focused on improving methodological details, whereas less attention has been paid to exploring the ...

The internet of things, social media and other technological developments have a created a situation in which more and more sensitive data is being exchanged between government and semi-government organizations. However, sharing confidential data ...

Defective components within solar photovoltaic (PV) arrays overheat, resulting in particular temperature patterns under the long-wave thermal infrared (LWIR) spectrum. The detection and on-field localization of these patterns is of paramount aid ...

Consistently high data quality is essential for the development of novel loss functions and architectures in the field of deep learning. The existence of such data and labels is usually presumed, while acquiring high-quality datasets is still a ...

Unconditional human image generation is an important task in vision and graphics, enabling various applications in the creative industry. Existing studies in this field mainly focus on “network engineering” such as designing new components and ...

• Our work demonstrates the redundance of public dataset and emphases data quality assessment.
• Multi-Branch data quality assessment method is proposed to measure the sample information.
• A data quality analysis method is proposed to ...

Deep learning has played a crucial role in the field of smart agriculture and been widely used in various applications. However, the deep learning models are constrained by data quality, which means poor data quality and unreliable data ...

Labeling for pathology detection is a laborious task, performed by highly trained and expensive experts. Datasets often have mixed formats, including a mix of pathology positional labels and categorical labels. Successfully combining mixed-format ...

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• Practitioner guidelines for the number of fruit to label for deep learning.
• ...

Due to the rapid development of deep learning, object detection models have become the current tool of choice for on-tree fruit detection in precision agriculture. The pipeline of fruit detection based on deep learning generally starts ...

Cloud computing is a model of distributed systems. This system allows users to access virtual resources including the processing power, storage, applications, etc. Storage as a Service (SaaS) is one of the cloud computing services. ...

• Cloud storage systems provide the storage service for the end-users.
• Cloud ...

The Internet of Underwater Things (IoUT) advances our ability in exploring oceans, lakes and rivers through multiple communication technologies that connect stationary and mobile nodes underwater, at the surface and in the sky. However, characteristics ...

The main mission of smart cities is to offer core infrastructure and quality of life to its citizens. This quality of life can be achieved by providing a cleaner and sustainable environment. However, the main mission of smart cities is undermined due to ...

The Business Process Management field addresses design, improvement, management, support, and execution of business processes. In doing so, we argue that it focuses more on developing modeling notations and process design approaches than on the needs ...

Data-Centric Publish-Subscribe (DCPS) is an architectural and communication paradigm where applications exchange data-content through a common data-space using publish-subscribe interactions. Due to its focus on data-content, DCPS is especially suitable ...

Wireless Sensor Network (WSN) is a collection of thousands of tiny sensor nodes having capability of wireless communication, limited computation and sensing. It is now used in many application including military, environmental, healthcare application, ...

The vision of data-centric security promises to enable efficient security in future ubiquitous computing environments, which are heavily pervaded with embedded devices and generally to complex to manage manually. We survey the existing work of various ...

The demand for efficient data dissemination/access techniques to find relevant data from within a sensor network has led to the development of Data-Centric Sensor (DCS) networks, where the sensor data instead of sensor nodes are named based on ...

Mobile nodes in some challenging network scenarios, e.g. battlefield and disaster recovery scenarios, suffer from intermittent connectivity and frequent partitions. Disruption Tolerant Network (DTN) technologies are designed to enable communications in ...

The rapidly increasing complexity of integrated circuit design is evolving to a more data-centric design scenario that supports sharing of design information. This paper presents the universal data model platform (UDMP) which introduce the data-centric ...

This paper presents the design of Pool, an efficient and scalable data storage scheme for supporting multidimensional queries. The foundation of the work that makes the Pool approach superior in executing multi-dimensional queries is that it provides a ...