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...

Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

This article’s main contributions are twofold: 1) to demonstrate how to apply the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does “trustworthy AI” mean at the time of the COVID-19 pandemic. To this end, we...

Artificial intelligence in breast-specific gamma imaging: Exploring the possibilities of automation of breast cancer detection and classification

Introduction Breast cancer is the most frequently diagnosed type of cancer in women in 2020. Treatment and prognosis of breast cancer is highly dependent on early and accurate diagnosis. In recent years, many studies have evaluated the use of artificial intelligence for the detection of breast cancer in mammographic images. Another imaging...

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...

Enabling Log Recommendation Through Machine Learning on Source Code

Logging is a common practice in software development that assists developers with the maintenance of software. Logging a system optimally is a challenging task, thus Li et al. have proposed a state-of-the-art log recommendation model. However, no further attempts exist to improve the model or reproduce their results using different training data...

Efficient Neural Architecture Search for Language Modeling

Neural networks have achieved great success in many difficult learning tasks like image classification, speech recognition and natural language processing. However, neural architectures are hard to design, which requires lots of knowledge and time of human experts. Therefore, there has been a growing interest in automating the process of designing...

Defining Ally’s Interactions: A Deep Learning framework to create a personalised interaction between users and a medical pod

Ally, is an intelligent, voice activated medical device concept that users talk to on a routine basis to log details regarding their health and well-being. The goal of this thesis is to create a personalised interaction between users and Ally. The user group is segregated into three generations; Baby Boomers, Generation X and Millennials. A...