Explainable artificial intelligence: a systematic review

G Vilone, L Longo - arXiv preprint arXiv:2006.00093, 2020 - arxiv.org
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …

Classification of explainable artificial intelligence methods through their output formats

G Vilone, L Longo - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
Machine and deep learning have proven their utility to generate data-driven models with
high accuracy and precision. However, their non-linear, complex structures are often difficult …

Explainable reinforcement learning in production control of job shop manufacturing system

A Kuhnle, MC May, L Schäfer… - International Journal of …, 2022 - Taylor & Francis
Manufacturing in the age of Industry 4.0 can be characterised by a high product variety and
complex material flows. The increasing individualisation of products requires adaptive …

Sketch2Code: transformation of sketches to UI in real-time using deep neural network

V Jain, P Agrawal, S Banga, R Kapoor… - arXiv preprint arXiv …, 2019 - arxiv.org
User Interface (UI) prototyping is a necessary step in the early stages of application
development. Transforming sketches of a Graphical User Interface (UI) into a coded UI …

Salience models: A computational cognitive neuroscience review

S Krasovskaya, WJ MacInnes - Vision, 2019 - mdpi.com
The seminal model by Laurent Itti and Cristoph Koch demonstrated that we can compute the
entire flow of visual processing from input to resulting fixations. Despite many replications …

A Fully Automated Global Post-hoc Method Based on Abstract Argumentation for Explainable Artificial Intelligence and its Application on Fully Connected Dense Deep …

G Vilone - 2024 - arrow.tudublin.ie
Abstract Explainable Artificial Intelligence (XAI) has rapidly grown in the past decade due to
the prevalence of machine learning, especially deep learning, in fields like healthcare and …

[PDF][PDF] Learning Selection Masks for Deep Neural Networks

S Oehmcke, F Gieseke - CoRR, 2019 - researchgate.net
Data have often to be moved between servers and clients during the inference phase. For
instance, modern virtual assistants collect data on mobile devices and the data are sent to …