About
5
Publications
479
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
8
Citations
Introduction
Manuel Silva (Member, IEEE) was born in Valparaíso, Chile, in 1990. He received the B.S. degree in electronics engineering and the M.Sc. degree in electrical engineering from the School of Electrical Engineering, Pontificia Universidad Católica de Valparaíso (PUCV), in 2022 and 2023, respectively. He is currently Ph.D. candidate in electrical engineering with the Robotics and Vision Laboratory, PUCV. His research interests include computer vision, remote sensing, machine learning, and robotics.
Current institution
Additional affiliations
March 2023 - present
Education
March 2023 - December 2026
February 2021 - November 2022
February 2019 - June 2022
Publications
Publications (5)
Chile’s mining industry, a global leader in copper production, faces challenges due to increasing volumes of mining waste, particularly Waste Rock Dumps (WRD) and LeachingWaste Dumps (LWD). The National Service of Geology and Mining (SERNAGEOMIN) requires assessment of the physical stability (PS) of these facilities, but current methods are hindere...
MineWaste Storage Facilities (MWSFs) in Chile present substantial environmental and safety risks due to their extensive scale and the hazardous nature of their contents. This study proposes an automated detection approach that integrates Sentinel-2 satellite imagery with advanced deep learning models to address these critical issues. A central cont...
In the global mining industry, periodic monitoring of large Mining Waste Deposits (MWDs) is essential. This paper presents an innovative approach leveraging advanced artificial intelligence techniques combined with high-resolution Sentinel satellite imagery to accurately geolocate MWDs in Chile. Our methodology involves segmenting satellite images,...
In this paper, we introduce a cutting-edge system that leverages state-of-the-art deep learning methodologies to generate high-quality synthetic thermal face images. Our unique approach integrates a thermally fine-tuned Stable Diffusion Model with a Vision Transformer (ViT) classifier, augmented by a Prompt Designer and Prompt Database for precise...
This article presents a method to detect and segment mine waste deposits, specifically waste rock dumps and leaching wasted dumps, in Sentinel-2 satellite imagery using artificial intelligence. This challenging task has important implications for mining companies and regulators like the National Geology and Mining Service in Chile. Challenges inclu...
