Trustworthy and Explainable Artificial Intelligence: an interdisciplinary perspective

Abstract

Artificial Intelligence (AI) is increasingly transforming the way image data is processed, analyzed and used to support decision-making in critical domains. From improving diagnostic accuracy in medical imaging to enabling precision monitoring in agriculture and ensuring quality control in industrial production. AI image analysis has become central to a wide range of applications.

This session focuses on practical and theoretical advances in applying machine learning, deep learning and computer vision techniques to real world image analysis tasks. Innovative methodologies, deployment strategies and current challenges to image analysis are topics of
interest in this special session. Emphasis is placed on approaches that demonstrate robustness, explainability and effectiveness in real scenarios in which images with high resolution are needed. Relevant topics include the entire pipeline of intelligent image processing, from data acquisition and annotation to model training, validation, deployment and post-hoc interpretation.

This session provides a chance to present both theoretical and applied research that extends the boundaries of what intelligent systems can achieve with visual data in several areas of knowledge such as healthcare, agriculture and manufacturing.

Topics

● Trustworthiness
● Non-discrimination and fairness
● Risk management
● Human intervention
● Explainabitlity and interpretability

Organizers

Manuel Germán Morales. University of Jaén, Spain. (mgerman@ujaen.es)
Ángel M. García Vico. University of Jaén, Spain. (agvico@ujaen.es)
Cristóbal J. Carmona. University of Jaén, Spain. (ccarmona@ujaen.es)

Submission

See submission instructions for the conference at the call for papers. At the beginning of the submission, please choose the track “Trustworthy and Explainable Artificial Intelligence: an interdisciplinary perspective”.

Submission link: https://easychair.org/conferences/?conf=ideal2025

Special Session Papers Submission Deadline: July 1st, 2025