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Pattern Recognition de Osslan Osiris Vergara-Villegas

Pattern Recognition: Lecture Notes in Computer Science

Editat de Osslan Osiris Vergara-Villegas, Vianey Guadalupe Cruz-Sánchez, Juan Humberto Sossa-Azuela, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López
en Limba Engleză Paperback – 11 iun 2022
This book constitutes the proceedings of the 14th Mexican Conference on Pattern Recognition, MCPR 2022, which was held in planned to be held Ciudad Juárez, Mexico, in June 2022.
The 33 papers presented in this volume were carefully reviewed and selected from 66 submissions. They are organized in the following topical sections: pattern recognition techniques; neural networks and deep learning; image and signal processing and analysis; natural language processing and recognition; robotics and remote sensing applications of pattern recognition; medical applications of pattern recognition.
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Specificații

ISBN-13: 9783031077494
ISBN-10: 3031077490
Pagini: 388
Ilustrații: XIV, 372 p. 151 illus., 114 illus. in color.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.59 kg
Ediția:1st edition 2022
Editura: Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Pattern Recognition Techniques.- Hot Spots & Hot Regions Detection using Classification Algorithms in BMPs Complexes at the Protein-protein Interface with the Ground-state Energy Feature.- Clustering of Twitter Networks based on Users’ Structural Profile.- Changing Model from NGSIM Dataset.- A Robust Fault Diagnosis Method in Presence of Noise and Missing Information for Industrial Plants.- A Preliminary Study of SMOTE on Imbalanced Big Datasets when Dealing with Sparse and Dense High Dimensionality.- A Novel Survival Analysis-based Approach for Predicting Behavioral Probability of Mining Mixed Data Bases using Machine Learning Algorithms.- Networks and Deep Learning A CNN-based Driver’s Drowsiness and Distraction Detection System.- 3D Convolutional Neural Network to Enhance Small-Animal Positron Emission Tomography Images in the Sinogram Domain.- Learning Dendrite Morphological Neurons Using Linkage Trees for Pattern Classification.- Deep Variational Method with Attention for High-Definition Face Generation.- Indoor Air Pollution Forecasting using Deep Neural Networks.-  Extreme Machine Learning Architectures based on Correlation.- Image & Signal Processing and Analysis Evaluating New Set of Acoustical Features for Cry Signal Classification.- Motor Imagery Classification Using Riemannian Geometry in Multiple Frequency Bands with a Weighted Nearest Neighbors Approach.- Virtualizing 3D Real Environments Using 2D Pictures Based on Photogrammetry.- Factorized U-net for Retinal Vessel Segmentation.- Multi-view Learning for EEG Signal Classification of Imagined Speech.- Escalante Emotion Recognition using Time-frequency Distribution and GLCM Features from EEG Signals.- Natural Language Processing and Recognition Leveraging Multiple Characterizations of Social Media Users for Depression Detection Using Data Fusion.- A Wide & Deep Learning Approach for Covid-19 Tweet Classification.- Does this Tweet Report an Adverse Drug Reaction? An Enhanced BERT-based Method to Identify Drugs Side Effects in Twitter.- We Will Know Them by Their Style: Fake News Detection based on Masked n-grams.- Multi-Document Text Summarization based on Genetic Algorithm and the Relevance of Sentence Features.- ´ Robotics & Remote Sensing Applications of Pattern Recognition On Labelling Pointclouds with the Nearest Facet of Triangulated Building Models.- Dust Deposition Classification on the Receiver Tube of the Parabolic Trough Collector: A Deep Learning-based Approach.- Detection of Pain Caused By A Thermal Stimulus Using EEG and Machine Learning.- Data Mining.- Natural Language Processing and Recognition.- Document Processing and Recognition.- Fuzzy and Hybrid Techniques in Pattern Recognition.- Image Coding, Processing and Analysis.- Industrial and Medical Applications of Pattern Recognition.- Bioinformatics.- Logical Combinatorial Pattern Recognition.- Mathematical Morphology.- Artificial Intelligence Techniques and Recognition.- Pattern Recognition Principles.- Robotics& Remote Sensing Applications of Pattern Recognition.- Shape and Texture Analysis.- Signal Processing and Analysis.