Advances in medical image analysis with vision transformers: a comprehensive review

R Azad, A Kazerouni, M Heidari, EK Aghdam… - Medical Image …, 2024 - Elsevier
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

[HTML][HTML] Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges

SO Abioye, LO Oyedele, L Akanbi, A Ajayi… - Journal of Building …, 2021 - Elsevier
The growth of the construction industry is severely limited by the myriad complex challenges
it faces such as cost and time overruns, health and safety, productivity and labour shortages …

Opportunities and adoption challenges of AI in the construction industry: A PRISMA review

M Regona, T Yigitcanlar, B **a, RYM Li - Journal of open innovation …, 2022 - mdpi.com
Artificial intelligence (AI) is a powerful technology with a range of capabilities, which are
beginning to become apparent in all industries nowadays. The increased popularity of AI in …

Algorithms to estimate Shapley value feature attributions

H Chen, IC Covert, SM Lundberg, SI Lee - Nature Machine Intelligence, 2023 - nature.com
Feature attributions based on the Shapley value are popular for explaining machine
learning models. However, their estimation is complex from both theoretical and …

Explainable ai: A review of machine learning interpretability methods

P Linardatos, V Papastefanopoulos, S Kotsiantis - Entropy, 2020 - mdpi.com
Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …

Transformer interpretability beyond attention visualization

H Chefer, S Gur, L Wolf - … of the IEEE/CVF conference on …, 2021 - openaccess.thecvf.com
Self-attention techniques, and specifically Transformers, are dominating the field of text
processing and are becoming increasingly popular in computer vision classification tasks. In …

[HTML][HTML] A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations …

IU Ekanayake, DPP Meddage, U Rathnayake - Case Studies in …, 2022 - Elsevier
Abstract Machine learning (ML) techniques are often employed for the accurate prediction of
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …

Knowledge neurons in pretrained transformers

D Dai, L Dong, Y Hao, Z Sui, B Chang, F Wei - arxiv preprint arxiv …, 2021 - arxiv.org
Large-scale pretrained language models are surprisingly good at recalling factual
knowledge presented in the training corpus. In this paper, we present preliminary studies on …

[HTML][HTML] Explainable AI for operational research: A defining framework, methods, applications, and a research agenda

KW De Bock, K Coussement, A De Caigny… - European Journal of …, 2024 - Elsevier
The ability to understand and explain the outcomes of data analysis methods, with regard to
aiding decision-making, has become a critical requirement for many applications. For …

Interpretable deep learning: Interpretation, interpretability, trustworthiness, and beyond

X Li, H **ong, X Li, X Wu, X Zhang, J Liu, J Bian… - … and Information Systems, 2022 - Springer
Deep neural networks have been well-known for their superb handling of various machine
learning and artificial intelligence tasks. However, due to their over-parameterized black-box …