QuantImage v2: a comprehensive and integrated physician-centered cloud platform for radiomics and machine learning research

Background: Radiomics, the field of image-based computational medical biomarker research, has experienced rapid growth over the past decade due to its potential to revolutionize the development of personalized decision support models. However, despite its research momentum and important advances toward methodological standardization, the...

A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services

Autonomous driving services depends on active sensing from modules such as camera, LiDAR, radar, and communication units. Traditionally, these modules process the sensed data on high-performance computing units inside the vehicle, which can deploy intelligent algorithms and AI models. The sensors mentioned above can produce large volumes of data...

Deep learning for detecting macroplastic litter in water bodies: A review

Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic environments, and causes economic and health problems. Accurate detection of macroplastic litter (plastic items >5 mm) in water is essential to estimate the quantities, compositions and sources, identify emerging trends, and design preventive...

Optimising High-Rise Buildings for Self-Sufficiency in Energy Consumption and Food Production Using Artificial Intelligence: Case of Europoint Complex in Rotterdam

The increase in global population, which negatively affects energy consumption, CO2 emissions, and arable land, necessitates designing sustainable habitation alternatives. Self-sufficient high-rise buildings, which integrate (electricity) generation and efficient usage of resources with dense habitation, can be a sustainable solution for future...

An interactive assessment framework for residential space layouts using pix2pix predictive model at the early-stage building design

Purpose: In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design. Design/methodology/approach: A methodology using an image-based deep learning model called pix2pix is proposed...

The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making

Governments look at explainable artificial intelligence's (XAI) potential to tackle the criticisms of the opaqueness of algorithmic decision-making with AI. Although XAI is appealing as a solution for automated decisions, the wicked nature of the challenges governments face complicates the use of XAI. Wickedness means that the facts that define...

Ceci n’est pas une Chaise:: Emerging Practices in Designer-AI Collaboration

Emerging practices of using ‘off the shelf’ AI as a creative partner in design processes are receiving increasing attention in design research. This paper takes the well-known concept of ‘framing’ in design, along with the Schönian concept of ‘surprise’ to explore how a human-AI dialogue could work. The approach taken is practice-based, with the...

Contestable AI by Design: Towards a Framework

As the use of AI systems continues to increase, so do concerns over their lack of fairness, legitimacy and accountability. Such harmful automated decision-making can be guarded against by ensuring AI systems are contestable by design: responsive to human intervention throughout the system lifecycle. Contestable AI by design is a small but...

Lane Detection using Spatio-Temporal Attention

Lane detection represents a fundamental task for automated/autonomous vehicles. Current lane detection methods do not provide the versatility of real-time performance, robustness,and accuracy required for real-world scenarios. The reasons include lack of computing power while being portable and inability to observe the continuity and structure...

Digital Excavation of Mediatized Urban Heritage: Automated Recognition of Buildings in Image Sources

Digital technologies provide novel ways of visualizing cities and buildings. They also facilitate new methods of analyzing the built environment, ranging from artificial intelligence (AI) to crowdsourced citizen participation. Digital representations of cities have become so refined that they challenge our perception of the real. However,...

Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy

As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation...

Politags: Breaking the filter bubble by using human computation techniques to enable diverse personalization

This research is aimed at breaking online political filter bubbles. We present a system that uses artificial intelligence and human computation to automatically collect article metadata on political content and thereby enables diverse personalization on content-serving platforms. This way, exploring alternative viewpoints could become as simple...

On domain-adaptive machine learning

Artificial intelligence, and in particular machine learning, is concerned with teaching computer systems to perform tasks. Tasks such as autonomous driving, recognizing tumors in medical images, or detecting suspicious packages in airports. Such systems learn by observing examples, i.e. data, and forming a mathematical description of what types...

Multi-sensor data fusion in a distributed environment; architectural solutions

The human operator observing the real world is confronted with a huge amount of data from multiple sensors observing that world. Multi-sensor data fusion (MSDF) is one of the emerging fields in advanced information processing, concerned with fusing sensor data from these multiple sensors. Automated MSDF can help the operator by processing sensor...