Image Recognition
Mostrando 1-12 de 203 artigos, teses e dissertações.
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1. Applicability of computer vision in seed identification: deep learning, random forest, and support vector machine classification algorithms
ABSTRACT The use of computer image analysis can assist the extraction of morphological information from seeds, potentially serving as a resource for solving taxonomic problems that require extensive training by specialists whose primary method of examination is visual identification. We propose to test the ability of deep learning, SVM and random forest algo
Acta Bot. Bras.. Publicado em: 2021-03
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2. LANDMARKS EVALUATION WITH USE OF QR-CODE FOR POSITIONING INDOOR ENVIRONMENT
Abstract: People tend to lose their sense of direction in closed environments and the role of indoor maps is to assist the user in navigating in these spaces, through understanding the environment, identifying reference points or positioning. Among the several forms of achieving positioning in indoor environments, this research used the method based on image
Bol. Ciênc. Geod.. Publicado em: 02/12/2019
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3. On the Improvement of Multiple Circles Detection from Images using Hough Transform
RESUMO A detecção de retas e curvas em imagens é uma tarefa de grande importância em diversas aplicações, como no reconhecimento de objetos e reconstrução de cenas. Apesar de haver fórmulas fechadas para o ajuste de curvas a um conjunto de pontos dados, se os pontos descrevem mais de uma instância do objeto, como dois círculos por exemplo, não h�
TEMA (São Carlos). Publicado em: 16/09/2019
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4. Mature pomegranate recognition methods in natural environments using machine vision
RESUMO: O uso de máquina para reconhecer romãs maduras em ambientes naturais é de grande importância para melhorar a aplicabilidade e a eficiência do trabalho de robôs de colheita. Ao analisar as características de cor das imagens coloridas de romãs maduras sob diferentes condições de iluminação, a viabilidade do modelo de cores YCbCr para o rec
Cienc. Rural. Publicado em: 02/09/2019
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5. Quantitative MRI data in Multiple Sclerosis patients: a pattern recognition study
Abstract Introduction Multiple Sclerosis (MS) is a neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Quantitative Magnetic Resonance Imaging (qMRI) enables a detailed characterization of brain tissue, but generates a large number of numerical results. In this study, we elucidated the main qMRI techniques a
Res. Biomed. Eng.. Publicado em: 28/05/2018
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6. 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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7. Face Image Retrieval of Efficient Sparse Code words and Multiple Attribute in Binning Image
ABSTRACT In photography, face recognition and face retrieval play an important role in many applications such as security, criminology and image forensics. Advancements in face recognition make easier for identity matching of an individual with attributes. Latest development in computer vision technologies enables us to extract facial attributes from the inp
Braz. arch. biol. technol.. Publicado em: 17/08/2017
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8. An Empirical Evaluation of the Local Texture Description Framework-Based Modified Local Directional Number Pattern with Various Classifiers for Face Recognition
ABSTRACT Texture is one of the chief characteristics of an image. In recent years, local texture descriptors have garnered attention among researchers in describing effective texture patterns to demarcate facial images. A feature descriptor titled Local Texture Description Framework-based Modified Local Directional Number pattern (LTDF_MLDN), capable of enco
Braz. arch. biol. technol.. Publicado em: 23/01/2017
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9. 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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10. 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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11. Micro-motion Recognition of Spatial Cone Target Based on ISAR Image Sequences
ABSTRACT The accurate micro-motions recognition of spatial cone target is the foundation of the characteristic parameter acquisition. For this reason, a micro-motion recognition method based on the distinguishing characteristics extracted from the Inverse Synthetic Aperture Radar (ISAR) sequences is proposed in this paper. The projection trajectory formula o
J. Aerosp. Technol. Manag.. Publicado em: 2016-06
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12. Proposing the novelty classifier for face recognition
INTRODUCTION: Face recognition, one of the most explored themes in biometry, is used in a wide range of applications: access control, forensic detection, surveillance and monitoring systems, and robotic and human machine interactions. In this paper, a new classifier is proposed for face recognition: the novelty classifier. METHODS: The performance of a novel
Rev. Bras. Eng. Bioméd.. Publicado em: 2014-12