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Autor Ribeiro, Bernardete |
Documentos disponibles escritos por este autor (3)
Crear una solicitud de compra Refinar búsqueda9th Iberian Conference, IbPRIA 2019, Madrid, Spain, July 1–4, 2019, Proceedings, Part I / Morales, Aythami ; Fierrez, Julian ; Sánchez, José Salvador ; Ribeiro, Bernardete
TÃtulo : 9th Iberian Conference, IbPRIA 2019, Madrid, Spain, July 1–4, 2019, Proceedings, Part I Tipo de documento: documento electrónico Autores: Morales, Aythami, ; Fierrez, Julian, ; Sánchez, José Salvador, ; Ribeiro, Bernardete, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XXXIII, 632 p. 297 ilustraciones, 247 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-31332-6 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Ordenador Sistemas de propósito especial y basados ​​en aplicaciones Estructuras aritméticas y lógicas Sistemas de reconocimiento de patrones Visión por computador Unidades aritméticas y lógicas informáticas. Reconocimiento Clasificación: 006.4 Resumen: Este conjunto de dos volúmenes constituye las actas arbitradas de la 9.ª Conferencia Ibérica sobre Reconocimiento de Patrones y Análisis de Imágenes, IbPRIA 2019, celebrada en Madrid, España, en julio de 2019. Los 99 artÃculos de estos volúmenes fueron cuidadosamente revisados ​​y seleccionados entre 137 presentaciones. Están organizados en secciones temáticas denominadas: Parte I: artÃculos mejor clasificados; aprendizaje automático; reconocimiento de patrones; procesamiento y representación de imágenes. Parte II: biometrÃa; análisis de escritura y documentos; otras aplicaciones. Nota de contenido: Best Ranked papers -- Towards a Joint Approach to Produce Decisions and Explanations Using CNNs -- Interactive-predictive neural multimodal systems -- Uncertainty estimation for black-box classification models: a use case for sentiment analysis -- Impact of ultrasound image reconstruction method on breast lesion classification with deep learning -- Segmentation of cell nuclei in fluorescence microscopy images using deep learning -- Food Recognition by Integrating Local and Flat Classifiers -- Machine Learning -- Combining Online Clustering and Rank Pooling Dynamics for Action Proposals -- On the Direction Guidance in Structure Tensor Total Variation Based Denoising -- Impact of Fused Visible-Infrared Video Streams on Visual Tracking -- Model Based Recursive Partitioning for Customized Price Optimization Analytics -- 3D Reconstruction of Archaeological Pottery from its Point Cloud -- Geometric interpretation of CNN's last layer -- Re-Weighted algorithms within the Lagrange duality framework: bringing interpretability to weights -- A note on Gradient-Based Intensity Normalization -- Blind Robust 3-D Mesh Watermarking based on Mesh Saliency and QIM quantization for Copyright Protection -- Using Copies to Remove Sensitive Data: A Case Study on Fair Superhero Alignment Prediction -- Weighted Multisource Tradaboost -- A proposal of neural networks with intermediate outputs -- Addressing the Big Data multi-class imbalance problem with oversampling and Deep Learning neural networks -- Reinforcement Learning and Neuroevolution in Flappy Bird Game -- Pattern Recognition -- Description and Recognition of Activity Patterns Using Sparse Vector Fields -- Instance Selection for the Nearest Neighbor Classifier Connecting the Performance to the Underlying Data Structure -- Modified DBSCAN algorithm for microscopic image analysis of wood -- Automatic Detection of Tuberculosis Bacilli from Microscopic Sputum Smear Images using Faster R-CNN, Transfer Learning and Augmentation -- Detection of stone circles in periglacial regions of Antarctica in UAV datasets -- Lesion Detection in Breast Ultrasound Images Using a Machine Learning Approach and Genetic Optimization -- Evaluating the Impact of Color Information in Deep Neural Networks -- Diatom classification including morphological adaptations using CNNs -- Deep Learning of Visual and Textual Data for Region Detection Applied to Item Coding -- Deep learning versus classic methods for multi-taxon diatom segmentation -- Estimation of Sulfonamides Concentration in Water based on Digital Colourimetry -- Characterization of cardiac and respiratory system of healthy subjects in supine and sitting position -- Automatic Fault Detection in a Cascaded Transformer Multilevel Inverter Using Pattern Recognition Techniques -- Collision anticipation via deep reinforcement learning for visual navigation -- Spectral band subset selection for discrimination of healthy skin and cutaneous Leishmanial ulcers -- Data Augmentation of Minority class with transfer learning for Classification of Imbalanced Breast Cancer Dataset using Inception V3 -- Image Processing and Representation -- Single-View Facial Hair 3D Reconstruction -- From Features to Attribute Graphs for Point Set Registration -- BELID: Boosted efficient local image descriptor -- A novel graph-based approach for seriation of mouse brain cross-section from images -- Class Reconstruction Driven Adversarial Domain Adaptation for Hyperspectral Image Classification -- Multi-Label Logo Classification using Convolutional Neural Networks -- Non-destructively prediction of quality parameters of drycured Iberian ham by applying computer vision and lowfield MRI -- Personalised aesthetics with residual adapters -- An Improvement for Capsule Networks using Depthwise Separable Convolution -- Wave Front Tracking in High Speed Videos Using a Dynamic Template Matching -- An Efficient Binary Descriptor to Describe Retinal Bifurcation Point for Image Registration -- Aggregation of deep features for image retrieval based on object detection -- Impact of Pre-Processing on Recognition of Cursive Video Text -- Image Feature Detection Based on Phase Congruency by Monogenic Filters with new Noise Estimation -- Texture Classification Using Capsule Networks -- Automatic vision based calibration system for planar cable-driven parallel robots -- 3D Non-rigid registration of Deformable object using GPU -- Focus estimation in academic environments using Computer Vision. Tipo de medio : Computadora Summary : This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019. The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named: Part I: best ranked papers; machine learning; pattern recognition; image processing and representation. Part II: biometrics; handwriting and document analysis; other applications. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] 9th Iberian Conference, IbPRIA 2019, Madrid, Spain, July 1–4, 2019, Proceedings, Part I [documento electrónico] / Morales, Aythami, ; Fierrez, Julian, ; Sánchez, José Salvador, ; Ribeiro, Bernardete, . - 1 ed. . - [s.l.] : Springer, 2019 . - XXXIII, 632 p. 297 ilustraciones, 247 ilustraciones en color.
ISBN : 978-3-030-31332-6
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Ordenador Sistemas de propósito especial y basados ​​en aplicaciones Estructuras aritméticas y lógicas Sistemas de reconocimiento de patrones Visión por computador Unidades aritméticas y lógicas informáticas. Reconocimiento Clasificación: 006.4 Resumen: Este conjunto de dos volúmenes constituye las actas arbitradas de la 9.ª Conferencia Ibérica sobre Reconocimiento de Patrones y Análisis de Imágenes, IbPRIA 2019, celebrada en Madrid, España, en julio de 2019. Los 99 artÃculos de estos volúmenes fueron cuidadosamente revisados ​​y seleccionados entre 137 presentaciones. Están organizados en secciones temáticas denominadas: Parte I: artÃculos mejor clasificados; aprendizaje automático; reconocimiento de patrones; procesamiento y representación de imágenes. Parte II: biometrÃa; análisis de escritura y documentos; otras aplicaciones. Nota de contenido: Best Ranked papers -- Towards a Joint Approach to Produce Decisions and Explanations Using CNNs -- Interactive-predictive neural multimodal systems -- Uncertainty estimation for black-box classification models: a use case for sentiment analysis -- Impact of ultrasound image reconstruction method on breast lesion classification with deep learning -- Segmentation of cell nuclei in fluorescence microscopy images using deep learning -- Food Recognition by Integrating Local and Flat Classifiers -- Machine Learning -- Combining Online Clustering and Rank Pooling Dynamics for Action Proposals -- On the Direction Guidance in Structure Tensor Total Variation Based Denoising -- Impact of Fused Visible-Infrared Video Streams on Visual Tracking -- Model Based Recursive Partitioning for Customized Price Optimization Analytics -- 3D Reconstruction of Archaeological Pottery from its Point Cloud -- Geometric interpretation of CNN's last layer -- Re-Weighted algorithms within the Lagrange duality framework: bringing interpretability to weights -- A note on Gradient-Based Intensity Normalization -- Blind Robust 3-D Mesh Watermarking based on Mesh Saliency and QIM quantization for Copyright Protection -- Using Copies to Remove Sensitive Data: A Case Study on Fair Superhero Alignment Prediction -- Weighted Multisource Tradaboost -- A proposal of neural networks with intermediate outputs -- Addressing the Big Data multi-class imbalance problem with oversampling and Deep Learning neural networks -- Reinforcement Learning and Neuroevolution in Flappy Bird Game -- Pattern Recognition -- Description and Recognition of Activity Patterns Using Sparse Vector Fields -- Instance Selection for the Nearest Neighbor Classifier Connecting the Performance to the Underlying Data Structure -- Modified DBSCAN algorithm for microscopic image analysis of wood -- Automatic Detection of Tuberculosis Bacilli from Microscopic Sputum Smear Images using Faster R-CNN, Transfer Learning and Augmentation -- Detection of stone circles in periglacial regions of Antarctica in UAV datasets -- Lesion Detection in Breast Ultrasound Images Using a Machine Learning Approach and Genetic Optimization -- Evaluating the Impact of Color Information in Deep Neural Networks -- Diatom classification including morphological adaptations using CNNs -- Deep Learning of Visual and Textual Data for Region Detection Applied to Item Coding -- Deep learning versus classic methods for multi-taxon diatom segmentation -- Estimation of Sulfonamides Concentration in Water based on Digital Colourimetry -- Characterization of cardiac and respiratory system of healthy subjects in supine and sitting position -- Automatic Fault Detection in a Cascaded Transformer Multilevel Inverter Using Pattern Recognition Techniques -- Collision anticipation via deep reinforcement learning for visual navigation -- Spectral band subset selection for discrimination of healthy skin and cutaneous Leishmanial ulcers -- Data Augmentation of Minority class with transfer learning for Classification of Imbalanced Breast Cancer Dataset using Inception V3 -- Image Processing and Representation -- Single-View Facial Hair 3D Reconstruction -- From Features to Attribute Graphs for Point Set Registration -- BELID: Boosted efficient local image descriptor -- A novel graph-based approach for seriation of mouse brain cross-section from images -- Class Reconstruction Driven Adversarial Domain Adaptation for Hyperspectral Image Classification -- Multi-Label Logo Classification using Convolutional Neural Networks -- Non-destructively prediction of quality parameters of drycured Iberian ham by applying computer vision and lowfield MRI -- Personalised aesthetics with residual adapters -- An Improvement for Capsule Networks using Depthwise Separable Convolution -- Wave Front Tracking in High Speed Videos Using a Dynamic Template Matching -- An Efficient Binary Descriptor to Describe Retinal Bifurcation Point for Image Registration -- Aggregation of deep features for image retrieval based on object detection -- Impact of Pre-Processing on Recognition of Cursive Video Text -- Image Feature Detection Based on Phase Congruency by Monogenic Filters with new Noise Estimation -- Texture Classification Using Capsule Networks -- Automatic vision based calibration system for planar cable-driven parallel robots -- 3D Non-rigid registration of Deformable object using GPU -- Focus estimation in academic environments using Computer Vision. Tipo de medio : Computadora Summary : This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019. The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named: Part I: best ranked papers; machine learning; pattern recognition; image processing and representation. Part II: biometrics; handwriting and document analysis; other applications. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : 9th Iberian Conference, IbPRIA 2019, Madrid, Spain, July 1–4, 2019, Proceedings, Part II Tipo de documento: documento electrónico Autores: Morales, Aythami, ; Fierrez, Julian, ; Sánchez, José Salvador, ; Ribeiro, Bernardete, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XXI, 534 p. 279 ilustraciones, 198 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-31321-0 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Visión por computador Sistemas de propósito especial y basados ​​en aplicaciones Estructuras aritméticas y lógicas Inteligencia artificial Reconocimiento de patrones automatizado Ordenador Sistemas de reconocimiento de patrones Unidades aritméticas Clasificación: 006.4 Resumen: Este conjunto de dos volúmenes constituye las actas arbitradas de la 9.ª Conferencia Ibérica sobre Reconocimiento de Patrones y Análisis de Imágenes, IbPRIA 2019, celebrada en Madrid, España, en julio de 2019. Los 99 artÃculos de estos volúmenes fueron cuidadosamente revisados ​​y seleccionados entre 137 presentaciones. Están organizados en secciones temáticas denominadas: Parte I: artÃculos mejor clasificados; aprendizaje automático; reconocimiento de patrones; procesamiento y representación de imágenes. Parte II: biometrÃa; análisis de escritura y documentos; otras aplicaciones. Nota de contenido: Biometrics -- What is the Role of Annotations in the Detection of Dermoscopic Structures? -- Keystroke Mobile Authentication: Performance of LongTerm Approaches and Combination with Behavioral-based Profiling -- Incremental Learning Techniques within a Self-updating Approach for Face Verification in Video-Surveillance -- Don't You Forget About Me: A Study on Long-Term Performance in ECG Biometrics -- Face Identification using Local Ternary Tree Pattern based Spatial Structural Components -- Catastrophic interference in Disguised Face Recognition -- Iris Center Localization Using Geodesic Distance and CNN -- Low-Light Face Image Enhancement based on Dynamic Face Part Selection -- Retinal Blood Vessel Segmentation: A semi-supervised approach -- Quality-based rPPG Heart Rate Estimation System for Driver Monitoring Using NIR Video Sequences -- Handwriting and Document Analysis -- Multi-Task Layout Analysis of Handwritten Musical Scores -- Domain Adaptation for Handwritten Symbol Recognition: A Case of Study in Old Music Manuscripts -- Approaching End-to-End Optical Music Recognition for Homophonic Scores -- Glyph and Position Classification of Music Symbols in Early Music Manuscripts -- Recognition of Arabic Handwritten Literal Amounts Using Deep Convolutional Neural Networks -- Offline Signature Verification using Textural Descriptors -- Pencil drawing of microscopic images through edge preserving filtering -- Line Segmentation Free Probabilistic Keyword Spotting and Indexing -- Other Applications -- Incremental Learning for Football Match Outcomes Prediction -- Frame by Frame Pain Estimation Using Locally Spatial Attention Learning -- Mosquito Larvae Image Classification based on DenseNet and Guided Grad-CAM -- Towards Automatic Rat's Gait Analysis Under Suboptimal Illumination Conditions -- Impact of Enhancement for Coronary Artery Segmentation Based on Deep Learning Neural Network -- Real-Time Traffic Monitoring with Occlusion Handling -- Image based estimation of fruit phytopathogenic lesions area -- A weakly-supervised approach for discovering common objects in airport video surveillance footage -- Standard Plenoptic Camera Calibration for a Range of Zoom and Focus Levels -- Going back to basics on volumetric segmentation of the lungs in CT: a fully image processing based technique -- Radiogenomics: Lung Cancer-Related Genes Mutation Status Prediction -- Learning to perform visual tasks from human demonstrations -- Serious Game Controlled by a Human-Computer Interface for Upper Limb Motor Rehabilitation: A Feasibility Study -- Weapon detection for particular scenarios using deep learning -- Hierarchical Deep Learning Approach for Plant Disease Detection -- An artificial vision based method for vehicle detection and classification in urban traffic -- Breaking Text-based CAPTCHA with Sparse Convolutional Neural Networks -- Image processing method for epidermal cells detection and measurement in Arabidopsis thaliana leaves -- User Modeling on Mobile Device based onFacial Clustering and Object Detection in Photos and Videos -- Gun and knife detection based on Faster R-CNN for video surveillance -- Painted Injection Moulded Part Surfaces -- A New Automatic Cancer Colony Forming Units Counting Method -- Deep Vesselness Measure from scale-space analysis of Hessian Matrix Eigenvalues -- Segmentation in Corridor Environments: Combining door and ceiling detection -- Development of a Fire Detection based on the Analysis of Video Data by means of Convolutional Neural Networks -- Towards automatic and robust particle tracking in microrheology studies -- Study of the impact of pre-processing applied to images acquired by the Cygno Experiment. Tipo de medio : Computadora Summary : This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019. The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named: Part I: best ranked papers; machine learning; pattern recognition; image processing and representation. Part II: biometrics; handwriting and document analysis; other applications. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] 9th Iberian Conference, IbPRIA 2019, Madrid, Spain, July 1–4, 2019, Proceedings, Part II [documento electrónico] / Morales, Aythami, ; Fierrez, Julian, ; Sánchez, José Salvador, ; Ribeiro, Bernardete, . - 1 ed. . - [s.l.] : Springer, 2019 . - XXI, 534 p. 279 ilustraciones, 198 ilustraciones en color.
ISBN : 978-3-030-31321-0
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Visión por computador Sistemas de propósito especial y basados ​​en aplicaciones Estructuras aritméticas y lógicas Inteligencia artificial Reconocimiento de patrones automatizado Ordenador Sistemas de reconocimiento de patrones Unidades aritméticas Clasificación: 006.4 Resumen: Este conjunto de dos volúmenes constituye las actas arbitradas de la 9.ª Conferencia Ibérica sobre Reconocimiento de Patrones y Análisis de Imágenes, IbPRIA 2019, celebrada en Madrid, España, en julio de 2019. Los 99 artÃculos de estos volúmenes fueron cuidadosamente revisados ​​y seleccionados entre 137 presentaciones. Están organizados en secciones temáticas denominadas: Parte I: artÃculos mejor clasificados; aprendizaje automático; reconocimiento de patrones; procesamiento y representación de imágenes. Parte II: biometrÃa; análisis de escritura y documentos; otras aplicaciones. Nota de contenido: Biometrics -- What is the Role of Annotations in the Detection of Dermoscopic Structures? -- Keystroke Mobile Authentication: Performance of LongTerm Approaches and Combination with Behavioral-based Profiling -- Incremental Learning Techniques within a Self-updating Approach for Face Verification in Video-Surveillance -- Don't You Forget About Me: A Study on Long-Term Performance in ECG Biometrics -- Face Identification using Local Ternary Tree Pattern based Spatial Structural Components -- Catastrophic interference in Disguised Face Recognition -- Iris Center Localization Using Geodesic Distance and CNN -- Low-Light Face Image Enhancement based on Dynamic Face Part Selection -- Retinal Blood Vessel Segmentation: A semi-supervised approach -- Quality-based rPPG Heart Rate Estimation System for Driver Monitoring Using NIR Video Sequences -- Handwriting and Document Analysis -- Multi-Task Layout Analysis of Handwritten Musical Scores -- Domain Adaptation for Handwritten Symbol Recognition: A Case of Study in Old Music Manuscripts -- Approaching End-to-End Optical Music Recognition for Homophonic Scores -- Glyph and Position Classification of Music Symbols in Early Music Manuscripts -- Recognition of Arabic Handwritten Literal Amounts Using Deep Convolutional Neural Networks -- Offline Signature Verification using Textural Descriptors -- Pencil drawing of microscopic images through edge preserving filtering -- Line Segmentation Free Probabilistic Keyword Spotting and Indexing -- Other Applications -- Incremental Learning for Football Match Outcomes Prediction -- Frame by Frame Pain Estimation Using Locally Spatial Attention Learning -- Mosquito Larvae Image Classification based on DenseNet and Guided Grad-CAM -- Towards Automatic Rat's Gait Analysis Under Suboptimal Illumination Conditions -- Impact of Enhancement for Coronary Artery Segmentation Based on Deep Learning Neural Network -- Real-Time Traffic Monitoring with Occlusion Handling -- Image based estimation of fruit phytopathogenic lesions area -- A weakly-supervised approach for discovering common objects in airport video surveillance footage -- Standard Plenoptic Camera Calibration for a Range of Zoom and Focus Levels -- Going back to basics on volumetric segmentation of the lungs in CT: a fully image processing based technique -- Radiogenomics: Lung Cancer-Related Genes Mutation Status Prediction -- Learning to perform visual tasks from human demonstrations -- Serious Game Controlled by a Human-Computer Interface for Upper Limb Motor Rehabilitation: A Feasibility Study -- Weapon detection for particular scenarios using deep learning -- Hierarchical Deep Learning Approach for Plant Disease Detection -- An artificial vision based method for vehicle detection and classification in urban traffic -- Breaking Text-based CAPTCHA with Sparse Convolutional Neural Networks -- Image processing method for epidermal cells detection and measurement in Arabidopsis thaliana leaves -- User Modeling on Mobile Device based onFacial Clustering and Object Detection in Photos and Videos -- Gun and knife detection based on Faster R-CNN for video surveillance -- Painted Injection Moulded Part Surfaces -- A New Automatic Cancer Colony Forming Units Counting Method -- Deep Vesselness Measure from scale-space analysis of Hessian Matrix Eigenvalues -- Segmentation in Corridor Environments: Combining door and ceiling detection -- Development of a Fire Detection based on the Analysis of Video Data by means of Convolutional Neural Networks -- Towards automatic and robust particle tracking in microrheology studies -- Study of the impact of pre-processing applied to images acquired by the Cygno Experiment. Tipo de medio : Computadora Summary : This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019. The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named: Part I: best ranked papers; machine learning; pattern recognition; image processing and representation. Part II: biometrics; handwriting and document analysis; other applications. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Introduction to Deep Learning Business Applications for Developers : From Conversational Bots in Customer Service to Medical Image Processing Tipo de documento: documento electrónico Autores: Vieira, Armando, ; Ribeiro, Bernardete, Mención de edición: 1 ed. Editorial: Berkeley, CA : Apress Fecha de publicación: 2018 Número de páginas: XXI, 343 p. 64 ilustraciones ISBN/ISSN/DL: 978-1-4842-3453-2 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Python (lenguaje de programa informático) Pitón Clasificación: 006.3 Resumen: Descubra las posibles aplicaciones, desafÃos y oportunidades del aprendizaje profundo desde una perspectiva empresarial con ejemplos técnicos. Estas aplicaciones incluyen reconocimiento, segmentación y anotación de imágenes, procesamiento y anotación de video, reconocimiento de voz, asistentes personales inteligentes, traducción automática y vehÃculos autónomos. Una Introducción a las aplicaciones empresariales de aprendizaje profundo para desarrolladores cubre algunos algoritmos DL comunes, como los algoritmos de recomendación basados ​​en contenido y el procesamiento del lenguaje natural. Explorará ejemplos, como la predicción de video con redes neuronales totalmente convolucionales (FCNN) y redes neuronales residuales (ResNets). También verá aplicaciones de DL para controlar la robótica, explorar el algoritmo de aprendizaje DeepQ con la búsqueda del árbol de Monte Carlo (utilizado para vencer a los humanos en el juego de Go) y modelar para la evaluación de riesgos financieros. También se mencionará el poderoso conjunto de algoritmos llamados redes neuronales generativas adversas (GAN) que se pueden aplicar para colorear y completar imágenes y transferir estilos. Después de leer este libro, tendrá una visión general del apasionante campo de las redes neuronales profundas y comprenderá la mayorÃa de las principales aplicaciones del aprendizaje profundo. El libro contiene algunos ejemplos de codificación, trucos e ideas sobre cómo entrenar modelos de aprendizaje profundo utilizando el marco Keras. Usted: Descubrirá sobre el aprendizaje profundo y por qué es tan poderoso Trabajará con los principales algoritmos disponibles para entrenar modelos de aprendizaje profundo Verá los principales avances en términos de aplicaciones de aprendizaje profundo Ejecutará ejemplos simples con una selección de bibliotecas de aprendizaje profundo Descubrirá las áreas de Impacto del aprendizaje profundo en los negocios. Nota de contenido: 1 Introduction -- 2 Deep Learning: An Overview -- 3 Deep Neural Network Models -- 4 Image Processing -- 5 Natural Language Processing and Speech -- 6 Reinforcement Learning and Robotics -- 7 Recommendations Algorithms and Advertising -- 8 Games and Art -- 9 Other Applications -- 10 Business Impact of DL Technology -- 11 New Research and Future Directions -- Appendix Training DNN with Keras. Tipo de medio : Computadora Summary : Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You'll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) that can be applied for image colorization, image completion, and style transfer. After reading this book you will have an overview of the exciting field of deep neural networks and an understanding of most of the major applications of deep learning. The book contains some coding examples, tricks, and insights on how to train deep learning models using the Keras framework. You will: Find out about deep learning and why it is so powerful Work with the major algorithms available to train deep learning models See the major breakthroughs in terms of applications of deep learning Run simple examples with a selection of deep learning libraries Discover the areas of impact of deep learning in business. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Introduction to Deep Learning Business Applications for Developers : From Conversational Bots in Customer Service to Medical Image Processing [documento electrónico] / Vieira, Armando, ; Ribeiro, Bernardete, . - 1 ed. . - Berkeley, CA : Apress, 2018 . - XXI, 343 p. 64 ilustraciones.
ISBN : 978-1-4842-3453-2
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Python (lenguaje de programa informático) Pitón Clasificación: 006.3 Resumen: Descubra las posibles aplicaciones, desafÃos y oportunidades del aprendizaje profundo desde una perspectiva empresarial con ejemplos técnicos. Estas aplicaciones incluyen reconocimiento, segmentación y anotación de imágenes, procesamiento y anotación de video, reconocimiento de voz, asistentes personales inteligentes, traducción automática y vehÃculos autónomos. Una Introducción a las aplicaciones empresariales de aprendizaje profundo para desarrolladores cubre algunos algoritmos DL comunes, como los algoritmos de recomendación basados ​​en contenido y el procesamiento del lenguaje natural. Explorará ejemplos, como la predicción de video con redes neuronales totalmente convolucionales (FCNN) y redes neuronales residuales (ResNets). También verá aplicaciones de DL para controlar la robótica, explorar el algoritmo de aprendizaje DeepQ con la búsqueda del árbol de Monte Carlo (utilizado para vencer a los humanos en el juego de Go) y modelar para la evaluación de riesgos financieros. También se mencionará el poderoso conjunto de algoritmos llamados redes neuronales generativas adversas (GAN) que se pueden aplicar para colorear y completar imágenes y transferir estilos. Después de leer este libro, tendrá una visión general del apasionante campo de las redes neuronales profundas y comprenderá la mayorÃa de las principales aplicaciones del aprendizaje profundo. El libro contiene algunos ejemplos de codificación, trucos e ideas sobre cómo entrenar modelos de aprendizaje profundo utilizando el marco Keras. Usted: Descubrirá sobre el aprendizaje profundo y por qué es tan poderoso Trabajará con los principales algoritmos disponibles para entrenar modelos de aprendizaje profundo Verá los principales avances en términos de aplicaciones de aprendizaje profundo Ejecutará ejemplos simples con una selección de bibliotecas de aprendizaje profundo Descubrirá las áreas de Impacto del aprendizaje profundo en los negocios. Nota de contenido: 1 Introduction -- 2 Deep Learning: An Overview -- 3 Deep Neural Network Models -- 4 Image Processing -- 5 Natural Language Processing and Speech -- 6 Reinforcement Learning and Robotics -- 7 Recommendations Algorithms and Advertising -- 8 Games and Art -- 9 Other Applications -- 10 Business Impact of DL Technology -- 11 New Research and Future Directions -- Appendix Training DNN with Keras. Tipo de medio : Computadora Summary : Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You'll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) that can be applied for image colorization, image completion, and style transfer. After reading this book you will have an overview of the exciting field of deep neural networks and an understanding of most of the major applications of deep learning. The book contains some coding examples, tricks, and insights on how to train deep learning models using the Keras framework. You will: Find out about deep learning and why it is so powerful Work with the major algorithms available to train deep learning models See the major breakthroughs in terms of applications of deep learning Run simple examples with a selection of deep learning libraries Discover the areas of impact of deep learning in business. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
