A Systematic Literature Review of artificial intelligence models in the domain of text, color, and object recognition revealed that architectures based on Convolutional Neural Networks (CNN) and deep learning models are the most effective for processing visual information through images or real-time video without deman...
Brian Delfino Flores Méndez, María Salomé Alejandre Apolinar, Hugo Amores Pérez et al.· Revista de Investigación en...· 0 citations
This chapter covers active fire detection using Bayesian Neural Networks (BNN), quantifying prediction uncertainty in wildfire mapping from satellite-derived thermal and reflectance data. It presents two case studies and a framework for uncertainty-aware ecological monitoring. Part of the EarthRISE Applied Artificial I...
Julia E. Harvie, Karlee E. Zammit, Brittany Engle et al.· Zenodo (CERN European Organi...· 0 citations
This chapter demonstrates semantic segmentation for crop type mapping, using Bhutan rice paddy mapping as the applied case study. It covers deep learning model development, training strategies, and evaluation using satellite imagery and Earth observation data. Part of the EarthRISE Applied Artificial Intelligence and D...
Biplov Bhandari, Timothy J. Mayer· Zenodo (CERN European Organi...· 0 citations
The NASA EarthRISE Applied Artificial Intelligence and Deep Learning Book provides practitioners with applied examples of Remote Sensing AI and Deep Learning across NASA Earth Action thematic areas. Each chapter focuses on a specific problem domain -- semantic segmentation, time series analysis, ecological process simu...
Timothy J. Mayer, Biplov Bhandari, David S. Saah· Zenodo (CERN European Organi...· 0 citations
This chapter applies deep learning semantic segmentation to detect selective logging events in tropical forests using very-high resolution satellite imagery. It covers data preparation, U-Net model training, and end-to-end inference workflows. Part of the EarthRISE Applied Artificial Intelligence and Deep Learning Book...
Osmar Yupanqui, Marvin Quispe· Zenodo (CERN European Organi...· 0 citations
This chapter demonstrates phenology-guided deep learning for soybean yield prediction using satellite-derived vegetation index time series, incorporating Bayesian uncertainty quantification for robust agricultural forecasting. Part of the EarthRISE Applied Artificial Intelligence and Deep Learning Book, Chapter 5: Time...
Chishan Zhang, Chunyuan Diao· Zenodo (CERN European Organi...· 0 citations
This chapter presents a deforestation segmentation model built on the Clay Earth observation foundation model, demonstrating how large pre-trained geospatial models can be fine-tuned for binary change detection using satellite imagery. Part of the EarthRISE Applied Artificial Intelligence and Deep Learning Book, Chapte...
Ate Poortinga, Daniel Marc G. dela Torre, Chanarun Saisaward et al.· Zenodo (CERN European Organi...· 0 citations
The integration of Generative Artificial Intelligence (GenAI) into English academic writing has attracted increasing attention, yet empirical evidence on learners’ acceptance of GenAI in undergraduate thesis writing remains limited. This study investigates Chinese EFL learners’ acceptance of GenAI tools in undergraduat...
Dataset Description WorldPT: A Structured Dataset of Fictional Worlds in Portuguese is a curated and fully structured dataset designed for the study, generation, and analysis of fictional universes (worldbuilding). The dataset organizes narrative elements into multiple interconnected categories, including characters, l...
L. R. Souza, Leopoldo André Dutra Lusquino Filho· Zenodo (CERN European Organi...· 0 citations
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.