The Brazilian court system is currently the most clogged up judiciary system in the world. Thousa... more The Brazilian court system is currently the most clogged up judiciary system in the world. Thousands of lawsuit cases reach the supreme court every day. These cases need to be analyzed in order to be associated to relevant tags and allocated to the right team. Most of the cases reach the court as raster scanned documents with widely variable levels of quality. One of the first steps for the analysis is to classify these documents. In this paper we present a Bidirectional Long Short-Term Memory network (Bi-LSTM) to classify these pieces of legal document.
Fronteiras: Journal of Social, Technological and Environmental Science, 2014
A história ambiental é um campo historiográfico relativamente novo. No entanto, seu desenvolvimen... more A história ambiental é um campo historiográfico relativamente novo. No entanto, seu desenvolvimento no campo científico tem se pautado pela utilização de ferramentas e metodologias que nem sempre foram utilizadas pela historiografia tradicional, sobretudo por lidar, de forma interdisciplinar com o meio ambiente. Esse artigo objetiva relacionar os estudos de geoprocessamento com as questões históricas, evidenciando o exercício do saber ambiental em sua dimensão interdisciplinar, auxiliando na quantificação das mudanças sofridas pelo meio ambiente no decorrer do tempo. Esse artigo procura refletir sobre o papel da tecnologia nas análises temporais para a uso histórico e também para o saber ambiental sobre efeitos perturbadores ao ambiente e à sustentabilidade.Palavras-chave: Geoprocessamento. História Ambiental. Saber Ambiental.
Abstract: The need to monitor the Earth’s surface over a range of spatial and temporal scales is ... more Abstract: The need to monitor the Earth’s surface over a range of spatial and temporal scales is fundamental in ecosystems planning and management. Change-Vector Analysis (CVA) is a bi-temporal method of change detection that considers the magnitude and direction of change vector. However, many multispectral applications do not make use of the direction component. The procedure most used to calculate the direction component using multiband data is the direction cosine, but the number of output direction cosine images is equal to the number of original bands and has a complex interpretation. This paper proposes a new approach to calculate the spectral direction of change, using the Spectral Angle Mapper and Spectral Correlation Mapper spectral-similarity measures. The chief advantage of this approach is that it generates a single image of change information insensitive to illumination variation. In this paper the magnitude component of the spectral similarity was calculated in two wa...
This work presents the evaluation of the P-band data discrimination properties using Fuzzy-ART ar... more This work presents the evaluation of the P-band data discrimination properties using Fuzzy-ART artificial neural network (AMN) unsupervised methodology for land cover mapping in the Amazon tropical forest.
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
Spectral classifiers identify a particular element from comparing the degree of adjustment betwee... more Spectral classifiers identify a particular element from comparing the degree of adjustment between the image spectrum and the reference spectrum that comes either from spectral libraries or from endmembers. However, these methods do not adopt the mixture concept integrally. The correlation of the mixture pixels should adopt not only the endmember spectra but also its mixture spectra. This limitation causes
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
Page 1. Normalization of Multi-Temporal Images Using a New Change Detection Method Based on the S... more Page 1. Normalization of Multi-Temporal Images Using a New Change Detection Method Based on the Spectral Classifier Osmar Abílio de Carvalho Júnior, Renato Fontes Guimarães, Roberto Arnaldo Trancoso Gomes, Ana Paula Ferreira ...
2007 IEEE International Geoscience and Remote Sensing Symposium, 2007
ABSTRACT A consistent data acquisition interval among multi-temporal images is necessary to accur... more ABSTRACT A consistent data acquisition interval among multi-temporal images is necessary to accurate landscape change detection and temporal-series signatures. Orbital images are difficult to maintain a temporal precision due to the different interferences that generate missing data. The correct handling of missing data is a difficult problem in data analysis and often depends on your specific situation. This missing information can be replaced using an interpolation method. In this paper is proposed a new algorithm that interpolates multitemporal images. This new computation method uses the cubic-spline interpolation technique to trace the reflectance and NDVI behaviors along time. The performance of the cubic-spline interpolation technique in the determination of NDVI temporal series is verified in terms of accuracy.
The objective of this study is to show the applicability of the genetic synthesis of the unsuperv... more The objective of this study is to show the applicability of the genetic synthesis of the unsupervised artificial neural network ART2 (Adaptive Resonance Theory) in the classification of ASTER image for land use/land cover mapping. The area under study is located in northern Mato Grosso State, Brazil, and is characterized by a strong human occupation process, which caused intensive changes at the landscape, by deforestation, selective logging and agriculture. Field data were acquired in May/June 2003. The use of ASTER data allowed an improvement of the analysis of the occupation process in tropical forest areas. ASTER images have adequate spatial and spectral resolution and are an alternative to the remaining remote sensing data available. The data had a correction of the cross-talk problem, after realized a resampling from SWIR bands (spatial resolution 30 to 15 m), a atmospheric correction and rectification of ASTER images from both data sets 2002 e 2003. The input parameters for t...
The Brazilian court system is currently the most clogged up judiciary system in the world. Thousa... more The Brazilian court system is currently the most clogged up judiciary system in the world. Thousands of lawsuit cases reach the supreme court every day. These cases need to be analyzed in order to be associated to relevant tags and allocated to the right team. Most of the cases reach the court as raster scanned documents with widely variable levels of quality. One of the first steps for the analysis is to classify these documents. In this paper we present a Bidirectional Long Short-Term Memory network (Bi-LSTM) to classify these pieces of legal document.
Fronteiras: Journal of Social, Technological and Environmental Science, 2014
A história ambiental é um campo historiográfico relativamente novo. No entanto, seu desenvolvimen... more A história ambiental é um campo historiográfico relativamente novo. No entanto, seu desenvolvimento no campo científico tem se pautado pela utilização de ferramentas e metodologias que nem sempre foram utilizadas pela historiografia tradicional, sobretudo por lidar, de forma interdisciplinar com o meio ambiente. Esse artigo objetiva relacionar os estudos de geoprocessamento com as questões históricas, evidenciando o exercício do saber ambiental em sua dimensão interdisciplinar, auxiliando na quantificação das mudanças sofridas pelo meio ambiente no decorrer do tempo. Esse artigo procura refletir sobre o papel da tecnologia nas análises temporais para a uso histórico e também para o saber ambiental sobre efeitos perturbadores ao ambiente e à sustentabilidade.Palavras-chave: Geoprocessamento. História Ambiental. Saber Ambiental.
Abstract: The need to monitor the Earth’s surface over a range of spatial and temporal scales is ... more Abstract: The need to monitor the Earth’s surface over a range of spatial and temporal scales is fundamental in ecosystems planning and management. Change-Vector Analysis (CVA) is a bi-temporal method of change detection that considers the magnitude and direction of change vector. However, many multispectral applications do not make use of the direction component. The procedure most used to calculate the direction component using multiband data is the direction cosine, but the number of output direction cosine images is equal to the number of original bands and has a complex interpretation. This paper proposes a new approach to calculate the spectral direction of change, using the Spectral Angle Mapper and Spectral Correlation Mapper spectral-similarity measures. The chief advantage of this approach is that it generates a single image of change information insensitive to illumination variation. In this paper the magnitude component of the spectral similarity was calculated in two wa...
This work presents the evaluation of the P-band data discrimination properties using Fuzzy-ART ar... more This work presents the evaluation of the P-band data discrimination properties using Fuzzy-ART artificial neural network (AMN) unsupervised methodology for land cover mapping in the Amazon tropical forest.
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
Spectral classifiers identify a particular element from comparing the degree of adjustment betwee... more Spectral classifiers identify a particular element from comparing the degree of adjustment between the image spectrum and the reference spectrum that comes either from spectral libraries or from endmembers. However, these methods do not adopt the mixture concept integrally. The correlation of the mixture pixels should adopt not only the endmember spectra but also its mixture spectra. This limitation causes
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
Page 1. Normalization of Multi-Temporal Images Using a New Change Detection Method Based on the S... more Page 1. Normalization of Multi-Temporal Images Using a New Change Detection Method Based on the Spectral Classifier Osmar Abílio de Carvalho Júnior, Renato Fontes Guimarães, Roberto Arnaldo Trancoso Gomes, Ana Paula Ferreira ...
2007 IEEE International Geoscience and Remote Sensing Symposium, 2007
ABSTRACT A consistent data acquisition interval among multi-temporal images is necessary to accur... more ABSTRACT A consistent data acquisition interval among multi-temporal images is necessary to accurate landscape change detection and temporal-series signatures. Orbital images are difficult to maintain a temporal precision due to the different interferences that generate missing data. The correct handling of missing data is a difficult problem in data analysis and often depends on your specific situation. This missing information can be replaced using an interpolation method. In this paper is proposed a new algorithm that interpolates multitemporal images. This new computation method uses the cubic-spline interpolation technique to trace the reflectance and NDVI behaviors along time. The performance of the cubic-spline interpolation technique in the determination of NDVI temporal series is verified in terms of accuracy.
The objective of this study is to show the applicability of the genetic synthesis of the unsuperv... more The objective of this study is to show the applicability of the genetic synthesis of the unsupervised artificial neural network ART2 (Adaptive Resonance Theory) in the classification of ASTER image for land use/land cover mapping. The area under study is located in northern Mato Grosso State, Brazil, and is characterized by a strong human occupation process, which caused intensive changes at the landscape, by deforestation, selective logging and agriculture. Field data were acquired in May/June 2003. The use of ASTER data allowed an improvement of the analysis of the occupation process in tropical forest areas. ASTER images have adequate spatial and spectral resolution and are an alternative to the remaining remote sensing data available. The data had a correction of the cross-talk problem, after realized a resampling from SWIR bands (spatial resolution 30 to 15 m), a atmospheric correction and rectification of ASTER images from both data sets 2002 e 2003. The input parameters for t...
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