Intrinsic Explainability for End-to-End Object Detection

Authors: Luis Fernandes, Joao N. D. Fernandes, Mariana Calado, Joao Ribeiro Pinto, Ricardo Cerqueira, Jaime S. Cardoso

Source: IEEE Access, Vol 12, Pp 2623-2634 (2024)

Subject Terms: Automated driving, healthcare, explainable AI, object detection, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/10373851/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/b7096987fd9145adbe39a2611c0d3068

Comprehensive Review: Machine and Deep Learning in Brain Stroke Diagnosis

Authors: João N. D. Fernandes, Vitor E. M. Cardoso, Alberto Comesaña-Campos, Alberto Pinheira

Source: Sensors, Vol 24, Iss 13, p 4355 (2024)

Subject Terms: brain stroke, deep learning, machine learning, classification, segmentation, object detection, Chemical technology, TP1-1185

File Description: electronic resource

Relation: https://www.mdpi.com/1424-8220/24/13/4355; https://doaj.org/toc/1424-8220

Access URL: https://doaj.org/article/5a94283d57ac47eca45189d4d49ad084

Explaining Bounding Boxes in Deep Object Detectors Using Post Hoc Methods for Autonomous Driving Systems

Authors: Caio Nogueira, Luís Fernandes, João N. D. Fernandes, Jaime S. Cardoso

Source: Sensors, Vol 24, Iss 2, p 516 (2024)

Subject Terms: explainable AI, autonomous driving, object detection, Chemical technology, TP1-1185

File Description: electronic resource

Relation: https://www.mdpi.com/1424-8220/24/2/516; https://doaj.org/toc/1424-8220

Access URL: https://doaj.org/article/d4a41cfab9be4c598fd72d52cce240f8

Life Cycle Analysis of a Steel Railway Bridge over the Operational Period considering Different Maintenance Scenarios: Application to a Case Study

Authors: João N. D. Fernandes, José C. Matos, Hélder S. Sousa, Mário R. F. Coelho

Source: Advances in Civil Engineering, Vol 2022 (2022)

Subject Terms: Engineering (General). Civil engineering (General), TA1-2040

File Description: electronic resource

Relation: https://doaj.org/toc/1687-8094

Access URL: https://doaj.org/article/3e074a1355334a35aeb0491524b79938