Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May 10-13, 2021, Revised Selected Papers

Gonzalez Hidalgo, Manuel; Papa, Joao Paulo; Tavares, Joao Manuel R. S.

Springer Nature Switzerland AG

01/2022

490

Mole

Inglês

9783030934194

15 a 20 dias

771

Descrição não disponível.
Medical Applications.- Predicting the use of Invasive Mechanical Ventilation in ICU COVID-19 patients.- A Coarse to Fine Corneal Ulcer Segmentation Approach using U-net and DexiNed in Chain.- Replacing Data Augmentation with Rotation-equivariant CNNs in Image-based Classification of Oral Cancer.- A Multitasking Learning Framework for Dermoscopic Image Analysis.- An Evaluation of Segmentation Techniques for COVID-19 Identification in Chest X-Ray.- A Study on Annotation Efficient Learning Methods for Segmentation in Prostate Histopathological Images.- Natural Language Processing.- Data-Augmented Emoji Approach to Sentiment Classification of Tweets.- Detecting Hate Speech in Cross-Lingual and Multi-Lingual Settings Using Language Agnostic Representations.- Prediction of Perception of Security Using Social Media Content.- Metaheuristics.- Fine-Tuning Dropout Regularization in Energy-Based Deep Learning.- Enhancing Hyper-To-Real Space Projections Through Euclidean NormMeta-Heuristic Optimization.- Using Particle Swarm Optimization With Gradient Descent For Parameter Learning In Convolutional Neural Networks.- Image Segmentation.- Object Delineation by Iterative Dynamic Trees.- Low-Cost Domain Adaptation for Crop and Weed Segmentation.- Databases.- MIGMA: The Facial Emotion Image Dataset forHuman Expression Recognition.- Construction of Brazilian Regulatory Traffic Sign Recognition Dataset.- Japanese Kana and Brazilian Portuguese manuscript database.- Skelibras: a Large 2d Skeleton Dataset of Dynamic Brazilian Signs.- Deep Learning.- Cricket Scene Analysis using the RetinaNet architecture. -Texture-Based Image Transformations for Improved Deep Learning Classification.- Towards Precise Recognition of Pollen Bearing Bees by Convolutional Neural Networks.- Web Application Attacks Detection Using Deep Learning.- Less is More: Accelerating Faster Neural Networks Straight from JPEG.- Optimizing Person Re-Identification using GeneratedAttention Masks.- Self-Supervised Bernoulli Autoencoders for Semi-Supervised Hashing.- Explainable Artificial Intelligence.- Interpretable Concept Drift.- Interpreting a Conditional Generative Adversarial Network Model for Crime Prediction.- Interpreting Decision Patterns in Financial Applications.- Image Processing.- Metal Artifact Reduction based on color mapping and inpainting techniques.- New Improvement in Obtaining Monogenic Phase Congruency.- Machine Learning.- Evaluating the Construction of Feature Descriptors in the Performance of the Image Data Stream Classification.- Clustering-based Partitioning of Water Distribution Networks for Leak Zone Location.- Bias Quantification for Protected Features in Pattern Classification Problems.- Regional Commodities Price Volatility Assessment Using Self-Driven Recurrent Networks.- Semi-supervised Deep Learning Based on Label Propagation in a 2D Embedded Space.- Iterative Creation of Matching-Graphs - Finding Relevant Substructures in Graph Sets.- Semi-Autogeonous (SAG) Mill Overload Forecasting.- Novel Time-Frequency Based Scheme for Detecting Sound Events from Sound Background in Audio Segments.- Computer Vision.- Generalized Conics with the Sharp Corners.- Automatic Face Mask Detection using a Hide and Seek Algorithm.- A Feature Extraction Approach Based on LBP Operator and Complex Networks for Face Recognition.- End-to-End Deep Sketch-to-Photo Matching Enforcing Realistic Photo Generation.- Forensic Analysis of Tampered Digital Photos.- COVID-19 Lung CT Images Recognition: A Feature-Based Approach.- A Topologically Consistent Color Digital Image Representation by a Single Tree.
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bioinformatics;cognitive and humanoid vision;computer systems;computer vision;deep learning;image analysis and intelligent data analysis;image processing;image quality;machine learning;neural networks;pattern recognition;pattern recognition and graphics;signal processing