Cargando…
Entropy as a High-Level Feature for XAI-Based Early Plant Stress Detection
This article is devoted to searching for high-level explainable features that can remain explainable for a wide class of objects or phenomena and become an integral part of explainable AI (XAI). The present study involved a 25-day experiment on early diagnosis of wheat stress using drought stress as...
Autores principales: | Lysov, Maxim, Maximova, Irina, Vasiliev, Evgeny, Getmanskaya, Alexandra, Turlapov, Vadim |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689005/ https://www.ncbi.nlm.nih.gov/pubmed/36359687 http://dx.doi.org/10.3390/e24111597 |
Ejemplares similares
-
Ensuring Explainability and Dimensionality Reduction in a Multidimensional HSI World for Early XAI-Diagnostics of Plant Stress
por: Lysov, Maxim, et al.
Publicado: (2023) -
Feature relevance XAI in anomaly detection: Reviewing approaches and challenges
por: Tritscher, Julian, et al.
Publicado: (2023) -
Hands-On Explainable AI (XAI) with Python
por: Rothman, Denis
Publicado: (2020) -
Editorial: Explainable Artificial Intelligence (XAI) in Systems Neuroscience
por: Lombardi, Angela, et al.
Publicado: (2021) -
Beauty is in the explainable artificial intelligence (XAI) of the “agnostic” beholder
por: Laios, Alexandros, et al.
Publicado: (2023)