A review of machine learning techniques in agroclimatic studies

D Tamayo-Vera, X Wang, M Mesbah - Agriculture, 2024 - mdpi.com
The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic
domain is pivotal for addressing the multifaceted challenges posed by climate change on …

Efficacy of automated machine learning models and feature engineering for diagnosis of equivocal appendicitis using clinical and computed tomography findings

J An, IS Kim, KJ Kim, JH Park, H Kang, HJ Kim… - Scientific Reports, 2024 - nature.com
This study evaluates the diagnostic efficacy of automated machine learning (AutoGluon) with
automated feature engineering and selection (autofeat), focusing on clinical manifestations …

[PDF][PDF] REVERSE ENGINEERING: TECHNIQUES, APPLICATIONS, CHALLENGES, OPPORTUNITIES

O Komolafe, IT Adejugbe, TI Olorunsola, JA Olowonubi… - academia.edu
This paper aims to provide a comprehensive overview of reverse engineering, discussing its
various techniques, applications, challenges, and opportunities. By exploring these aspects …

[ΑΝΑΦΟΡΑ][C] Juho An, Il Seok Kim 2, 8, Kwang‑Ju Kim 3, Ji Hyun Park 4, Hyuncheol Kang 5, Hyuk Jung Kim 6

YS Kim, JH Ahn - Scientific Reports, 2024