4 citations · 4 across the 2 of their papers we have counts for
7 papers · 1 filter
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…
MTLSegFormer: Multi-task Learning with Transformers for Semantic Segmentation in Precision Agriculture
Diogo Nunes Goncalves, Jose Marcato Junior, Pedro Zamboni +4
Multi-task learning has proven to be effective in improving the performance of correlated tasks. Most of the existing methods use a backbone to extract initial features with indepe…
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…
RADAM: Texture Recognition through Randomized Aggregated Encoding of Deep Activation Maps
Leonardo Scabini, Kallil M. Zielinski, Lucas C. Ribas +3
Texture analysis is a classical yet challenging task in computer vision for which deep neural networks are actively being applied. Most approaches are based on building feature agg…
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…
Dynamic texture analysis with diffusion in networks
Lucas C. Ribas, Wesley N. Goncalves, Odemir M. Bruno
Dynamic texture is a field of research that has gained considerable interest from computer vision community due to the explosive growth of multimedia databases. In addition, dynami…