Titlebook: Applications of Computational Intelligence; Second IEEE Colombia Alvaro David Orjuela-Cañón,Juan Carlos Figueroa-Ga Conference proceedings

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Classification of Satellite Images Using Rp Fuzzy C Meansncreasingly common access to satellite data. In this context. The investigation of techniques related to remote sensing becomes very important because it provide important information about the earth’s surface. Currently, segmentation is an essential step in applications that make use of satellite i

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A Feature Extraction Method Based on Convolutional Autoencoder for Plant Leaves Classificationent trees. While previous approaches relied on image processing and manual feature extraction, the proposed approach operates directly on the image pixels, without any preprocessing. Firstly, we use multiple layers of CAE to learn the features of leaf image dataset. Secondly, the extracted features

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Acquisition System Based in a Low-Cost Optical Architecture with Single Pixel Measurements and RGB Sial vehicles (UAVs), it is common to attach a spectral camera to an UAV to acquire information. Unfortunately, the spectral cameras used with UAV are expensive. Therefore this work proposes a low-cost optical architecture to acquire spectral images. The proposed architecture takes advantage of the U

周兴旺

Integration of an Adaptive Cellular Automaton and a Cellular Neural Network for the Impulsive Noise detection in grayscale images. In general, this procedure consists of: (1) implementing a cellular automaton (CA) with an adaptive behavior that expands the Moore neighborhood when it considers that the information obtained from its first level neighbors is insufficient. Based on the above, the ima

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Sweet Citrus Fruit Detection in Thermal Images Using Fuzzy Image Processingficiency of those systems is proposes a vision algorithm to estimate the amount of fruits in sweet orange trees. This study proposes a computer vision system based on the capture of thermal images and fuzzy image processing. A bibliographical review has been done to analyze the state-of-the-art of t

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1865-0929 bia, in June 2019. .The 21 full papers presented were carefully reviewed and selected from 59 submissions. The papers cover such topics as video processing; biomedical systems; image processing, etc. . .978-3-030-36210-2978-3-030-36211-9Series ISSN 1865-0929 Series E-ISSN 1865-0937

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https://doi.org/10.1007/978-3-662-45614-9s the tool to analyze this text and get some insight using Machine Learning Techniques. In this work, . is analyzed to detect social events because users are considered sensors. The analysis is performed over Brazilian tweets to detect dengue. The results show the utility of the proposal to recognize dengue epidemics in the Brazilian territory.

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https://doi.org/10.1007/978-3-658-31005-9xels, without any preprocessing. Firstly, we use multiple layers of CAE to learn the features of leaf image dataset. Secondly, the extracted features were used to train a linear classifier based on SVM. Experimental results show that the classifiers using these features can improve their predictive value, reaching an accuracy rate of 94.74%.

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Building Dengue Sensors for Brazil Using a Social Network and Text Minings the tool to analyze this text and get some insight using Machine Learning Techniques. In this work, . is analyzed to detect social events because users are considered sensors. The analysis is performed over Brazilian tweets to detect dengue. The results show the utility of the proposal to recognize dengue epidemics in the Brazilian territory.

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