Image Classification
Mostrando 25-36 de 311 artigos, teses e dissertações.
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25. Swingle citrumelo seed vigor and storability associated with fruit maturity classes based on RGB parameters
ABSTRACT: Citrus seeds normally have low storability. Identifying an optimal fruit harvest time for production of high vigor seeds is important for nurseries; however, identifying this stage for Swingle citrumelo fruits has been based only on visual color examination, and research related to this parameter has been inconsistent. The main objective of this st
Sci. agric. (Piracicaba, Braz.). Publicado em: 2017-10
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26. COMPARATIVE ASSESSMENT BETWEEN PER-PIXEL AND OBJECT-ORIENTED FOR MAPPING LAND COVER AND USE
ABSTRACT: The traditional per-pixel classification methods consider only spectral information, and may be limited. Object-based classifiers, however, also consider shape and texture, firstly segmenting the image, and then classifying individual objects. Thus, a Geographic Object-Based Image Analysis (GEOBIA) was compared in conjunction with data mining techn
Eng. Agríc.. Publicado em: 2017-09
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27. A System Based on Artificial Neural Networks for Automatic Classification of Hydro-generator Stator Windings Partial Discharges
Abstract Partial discharge (PD) monitoring is widely used in rotating machines to evaluate the condition of stator winding insulation, but its practice on a large scale requires the development of intelligent systems that automatically process these measurement data. In this paper, it is proposed a methodology of automatic PD classification in hydro-generato
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2017-09
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28. Breast density pattern characterization by histogram features and texture descriptors
Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective
Res. Biomed. Eng.. Publicado em: 06/04/2017
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29. Novel Image Classification technique using Particle Filter Framework optimised by Multikernel Sparse Representation
ABSTRACT The robustness and speed of image classification is still a challenging task in satellite image processing. This paper introduces a novel image classification technique that uses the particle filter framework (PFF)-based optimisation technique for satellite image classification. The framework uses a template-matching algorithm, comprising fast march
Braz. arch. biol. technol.. Publicado em: 23/01/2017
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30. Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran
ABSTRACT During the recent decades, deciduous forests have been molested by human intervention. Easy access, abundance and diversity of valuable forest products have led to increased population density, creating new residential areas and deforestation activities. Revealing changes is one of the fundamental methods in management and assessment of natural reso
An. Acad. Bras. Ciênc.. Publicado em: 2016-12
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31. Is It Possible to Classify Topsoil Texture Using a Sensor Located 800 km Away from the Surface?
ABSTRACT It is often difficult for pedologists to “see” topsoils indicating differences in properties such as soil particle size. Satellite images are important for obtaining quick information for large areas. However, mapping extensive areas of bare soil using a single image is difficult since most areas are usually covered by vegetation. Thus, the aim
Rev. Bras. Ciênc. Solo. Publicado em: 03/11/2016
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32. Breast tumor classification in ultrasound images using support vector machines and neural networks
Abstract Introduction The use of tools for computer-aided diagnosis (CAD) has been proposed for detection and classification of breast cancer. Concerning breast cancer image diagnosing with ultrasound, some results found in literature show that morphological features perform better than texture features for lesions differentiation, and indicate that a reduc
Res. Biomed. Eng.. Publicado em: 10/10/2016
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33. Taxonomic indexes for differentiating malignancy of lung nodules on CT images
Abstract Introduction Lung cancer remains the leading cause of cancer mortality worldwide, with one of the lowest survival rates after diagnosis. Therefore, early detection greatly increases the chances of improving patient survival. Methods This study proposes a method for diagnosis of lung nodules in benign and malignant tumors based on image processing
Res. Biomed. Eng.. Publicado em: 19/09/2016
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34. Image segmentation and particles classification using texture analysis method
Introduction: Ingredients of oily fish include a large amount of polyunsaturated fatty acids, which are important elements in various metabolic processes of humans, and have also been used to prevent diseases. However, in an attempt to reduce cost, recent developments are starting a replace the ingredients of fish oil with products of microalgae, that also p
Res. Biomed. Eng.. Publicado em: 09/09/2016
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35. Comparative study of periodicity estimation methods using ultrasonic signals
Abstract Introduction Various signal-processing techniques have been proposed to extract quantitative information about internal structures of tissues from the original radio frequency (RF) signals instead of an ultrasound image. The quantifiable parameter called the mean scatterer spacing (MSS) can be useful to detect changes in the quasi-periodic microstr
Res. Biomed. Eng.. Publicado em: 09/09/2016
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36. Software for micromorphometric characterization of soil pores obtained from 2-D image analysis
ABSTRACT Studies of soil porosity through image analysis are important to an understanding of how the soil functions. However, the lack of a simplified methodology for the quantification of the shape, number, and size of soil pores has limited the use of information extracted from images. The present work proposes a software program for the quantification an
Sci. agric. (Piracicaba, Braz.). Publicado em: 2016-08