Search Results for author: Jefersson A. dos Santos

Found 23 papers, 13 papers with code

FuSS: Fusing Superpixels for Improved Segmentation Consistency

1 code implementation6 Jun 2022 Ian Nunes, Matheus B. Pereira, Hugo Oliveira, Jefersson A. dos Santos, Marcus Poggi

In this work, we propose two different approaches to improve the semantic consistency of Open Set Semantic Segmentation.

Semantic Segmentation Superpixels

Seeing without Looking: Analysis Pipeline for Child Sexual Abuse Datasets

no code implementations29 Apr 2022 Camila Laranjeira, João Macedo, Sandra Avila, Jefersson A. dos Santos

The online sharing and viewing of Child Sexual Abuse Material (CSAM) are growing fast, such that human experts can no longer handle the manual inspection.

Pornography Detection

Conditional Reconstruction for Open-set Semantic Segmentation

1 code implementation2 Mar 2022 Ian Nunes, Matheus B. Pereira, Hugo Oliveira, Jefersson A. dos Santos, Marcus Poggi

Open set segmentation is a relatively new and unexploredtask, with just a handful of methods proposed to model suchtasks. We propose a novel method called CoReSeg thattackles the issue using class conditional reconstruction ofthe input images according to their pixelwise mask.

Semantic Segmentation

Weakly Supervised Few-Shot Segmentation Via Meta-Learning

no code implementations3 Sep 2021 Pedro H. T. Gama, Hugo Oliveira, José Marcato Junior, Jefersson A. dos Santos

Semantic segmentation is a classic computer vision task with multiple applications, which includes medical and remote sensing image analysis.

Few-Shot Semantic Segmentation Meta-Learning +1

Opening Deep Neural Networks with Generative Models

1 code implementation20 May 2021 Marcos Vendramini, Hugo Oliveira, Alexei Machado, Jefersson A. dos Santos

Image classification methods are usually trained to perform predictions taking into account a predefined group of known classes.

Image Classification Object Recognition +1

A Soft Computing Approach for Selecting and Combining Spectral Bands

no code implementations10 Nov 2020 Juan F. H. Albarracín, Rafael S. Oliveira, Marina Hirota, Jefersson A. dos Santos, Ricardo da S. Torres

We introduce a soft computing approach for automatically selecting and combining indices from remote sensing multispectral images that can be used for classification tasks.

Classification General Classification +1

AiRound and CV-BrCT: Novel Multi-View Datasets for Scene Classification

no code implementations3 Aug 2020 Gabriel Machado, Edemir Ferreira, Keiller Nogueira, Hugo Oliveira, Pedro Gama, Jefersson A. dos Santos

Despite a large number of public repositories for both georeferenced photographs and aerial images, there is a lack of benchmark datasets that allow the development of approaches that exploit the benefits and complementarity of aerial/ground imagery.

General Classification Image Classification +1

Fully Convolutional Open Set Segmentation

1 code implementation25 Jun 2020 Hugo Oliveira, Caio Silva, Gabriel L. S. Machado, Keiller Nogueira, Jefersson A. dos Santos

In semantic segmentation knowing about all existing classes is essential to yield effective results with the majority of existing approaches.

Open Set Learning Semantic Segmentation

BrazilDAM: A Benchmark dataset for Tailings Dam Detection

1 code implementation17 Mar 2020 Edemir Ferreira, Matheus Brito, Remis Balaniuk, Mário S. Alvim, Jefersson A. dos Santos

In the experiments, we achieved an average classification accuracy of 94. 11% in tailing dam binary classification task.

Binary Classification Classification +2

Towards Open-Set Semantic Segmentation of Aerial Images

no code implementations27 Jan 2020 Caio C. V. da Silva, Keiller Nogueira, Hugo N. Oliveira, Jefersson A. dos Santos

A more uncommon source of images exploited in the remote sensing field are satellite and aerial images.

Semantic Segmentation

An Introduction to Deep Morphological Networks

no code implementations4 Jun 2019 Keiller Nogueira, Jocelyn Chanussot, Mauro Dalla Mura, Jefersson A. dos Santos

Results show that the proposed DeepMorphNets is a promising technique that can learn distinct features when compared to the ones learned by current deep learning methods.

Image Classification

Truly Generalizable Radiograph Segmentation with Conditional Domain Adaptation

1 code implementation16 Jan 2019 Hugo Oliveira, Edemir Ferreira, Jefersson A. dos Santos

We merge these unsupervised networks with supervised deep semantic segmentation architectures in order to create a semi-supervised method capable of learning from both unlabeled and labeled data, whenever labeling is available.

General Classification Semantic Segmentation +2

A Comparative Study on Unsupervised Domain Adaptation Approaches for Coffee Crop Mapping

no code implementations6 Jun 2018 Edemir Ferreira, Mário S. Alvim, Jefersson A. dos Santos

In this work, we investigate the application of existing unsupervised domain adaptation (UDA) approaches to the task of transferring knowledge between crop regions having different coffee patterns.

Unsupervised Domain Adaptation

Dynamic Multi-Context Segmentation of Remote Sensing Images based on Convolutional Networks

1 code implementation11 Apr 2018 Keiller Nogueira, Mauro Dalla Mura, Jocelyn Chanussot, William R. Schwartz, Jefersson A. dos Santos

A systematic evaluation of the proposed algorithm is conducted using four high-resolution remote sensing datasets with very distinct properties.

Semantic Segmentation

A Genetic Algorithm Approach for ImageRepresentation Learning through Color Quantization

no code implementations18 Nov 2017 Érico M. Pereira, Ricardo da S. Torres, Jefersson A. dos Santos

Recently, data-driven feature learning approaches have been successfully explored as alternatives for producing more representative visual features.

Content-Based Image Retrieval Information Retrieval +3

Activity Recognition based on a Magnitude-Orientation Stream Network

no code implementations22 Aug 2017 Carlos Caetano, Victor H. C. de Melo, Jefersson A. dos Santos, William Robson Schwartz

The temporal component of videos provides an important clue for activity recognition, as a number of activities can be reliably recognized based on the motion information.

Activity Recognition Optical Flow Estimation

Meat adulteration detection through digital image analysis of histological cuts using LBP

no code implementations7 Nov 2016 João J. de Macedo Neto, Jefersson A. dos Santos, William Robson Schwartz

Food fraud has been an area of great concern due to its risk to public health, reduction of food quality or nutritional value and for its economic consequences.

Towards Better Exploiting Convolutional Neural Networks for Remote Sensing Scene Classification

1 code implementation4 Feb 2016 Keiller Nogueira, Otávio A. B. Penatti, Jefersson A. dos Santos

We present an analysis of three possible strategies for exploiting the power of existing convolutional neural networks (ConvNets) in different scenarios from the ones they were trained: full training, fine tuning, and using ConvNets as feature extractors.

General Classification Scene Classification

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