Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...

This repository is the code implementation of the paper Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A ...

Faculty of Philosophy, Sciences, and Letters at Ribeirão Preto (FFCLRP), Department of Chemistry, University of São Paulo (USP),Avenida Bandeirantes, 3900, Ribeirão Preto, São Paulo State 14040-901, ...

Eggplant seed vigor is a crucial indicator of its germination rate and seedling growth quality. In response to the need for efficient and nondestructive assessment methods, this study explores the use ...

Early detection of lung cancer in smokers using miRNA profiles and a hybrid deep learning framework. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...

Department of Preventive Medicine, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China Background: Effective connectivity (EC) refers to the ...

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...

Large language models (LLMs) are continually evolving by ingesting vast quantities of text data, enabling them to become more accurate predictors, reasoners, and conversationalists. Their learning ...

Abstract: Data mining classification techniques become increasingly relevant because it is sensible to bring meaningful patterns out from very large data sets; however, cross-comparison and comparison ...