462 citations · 698 across the 8 of their papers we have counts for
8 papers
Data Augmentation and Resolution Enhancement using GANs and Diffusion Models for Tree Segmentation
Alessandro dos Santos Ferreira, Ana Paula Marques Ramos, José Marcato Junior +1
Urban forests play a key role in enhancing environmental quality and supporting biodiversity in cities. Mapping and monitoring these green spaces are crucial for urban planning and…
The Segment Anything Model (SAM) for Remote Sensing Applications: From Zero to One Shot
Lucas Prado Osco, Qiusheng Wu, Eduardo Lopes de Lemos +4
Segmentation is an essential step for remote sensing image processing. This study aims to advance the application of the Segment Anything Model (SAM), an innovative image segmentat…
The Potential of Visual ChatGPT For Remote Sensing
Lucas Prado Osco, Eduardo Lopes de Lemos, Wesley Nunes Gonçalves +2
Recent advancements in Natural Language Processing (NLP), particularly in Large Language Models (LLMs), associated with deep learning-based computer vision techniques, have shown s…
Semantic Segmentation with Labeling Uncertainty and Class Imbalance
Patrik Olã Bressan, José Marcato Junior, José Augusto Correa Martins +8
Recently, methods based on Convolutional Neural Networks (CNN) achieved impressive success in semantic segmentation tasks. However, challenges such as the class imbalance and the u…
Counting and Locating High-Density Objects Using Convolutional Neural Network
Mauro dos Santos de Arruda, Lucas Prado Osco, Plabiany Rodrigo Acosta +8
This paper presents a Convolutional Neural Network (CNN) approach for counting and locating objects in high-density imagery. To the best of our knowledge, this is the first object…
A Deep Learning Approach Based on Graphs to Detect Plantation Lines
Diogo Nunes Gonçalves, Mauro dos Santos de Arruda, Hemerson Pistori +8
Deep learning-based networks are among the most prominent methods to learn linear patterns and extract this type of information from diverse imagery conditions. Here, we propose a…
A Review on Deep Learning in UAV Remote Sensing
Lucas Prado Osco, José Marcato Junior, Ana Paula Marques Ramos +7
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language,…
A CNN Approach to Simultaneously Count Plants and Detect Plantation-Rows from UAV Imagery
Lucas Prado Osco, Mauro dos Santos de Arruda, Diogo Nunes Gonçalves +11
In this paper, we propose a novel deep learning method based on a Convolutional Neural Network (CNN) that simultaneously detects and geolocates plantation-rows while counting its p…