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Intelligent Data Engineering and Automated Learning - IDEAL 2020

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This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International ... Weiterlesen
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This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.*

The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.

* The conference was held virtually due to the COVID-19 pandemic.


Prostate Gland Segmentation in Histology Images via Residual and Multi-Resolution U-Net.- Evaluation of Machine Learning Algorithms for Automated Management of Wireless Links.- Imputation of Missing Boarding Stop Information in Smart Card Data with Machine Learning Methods.- HEAT: Hyperbolic Embedding of Attributed Networks.- Least Squares Approach for Multivariate Split Selection in Regression Trees.- A Framework for the Multi-modal Analysis of Novel Behavior in Business Processes.- A Novel Metaheuristic Approach for Loss Reduction and Voltage Profile Improvement in Power Distribution Networks based on Simultaneous Placement and Sizing of Distributed Generators and Shunt Capacitor Banks.- Simple Effective Methods for Decision-Level Fusion in Two-Stream Convolutional Neural Networks for Video Classification.- LSI Based Mechanism for Educational Videos Retrieval by Transcripts Processing.- Visualization of Numerical Association Rules by Hill Slopes.- Adaptation and Anxiety Assessment in Undergraduate Nursing Students.- Text Similarity between Concepts Extracted from Source Code and Documentation.- Using Kullback-Leibler Divergence to Identify Prominent Sensor Data for Fault Diagnosis.- An Analysis of Protein Patterns Present in the Saliva of Diabetic Patients using Pairwise Relationship and Hierarchical Clustering.- Improving Adversarial Learning with Image Quality Measures for Image Deblurring.- On Random-Forest-Based Prediction Intervals.-A Machine Learning Approach to Forecast the Safest Period for Outdoor Sports.-One-Shot Only Real-Time Video Classification: A Case Study in Facial Emotion Recognition.- Integrating a Data Mining Engine into Recommender Systems.- Free-Floating Carsharing in SimFleet.- Fatigue Detection in Strength Exercises for Older People.- Trading Cryptocurrency with Deep Deterministic Policy Gradients.- TMSA: Participatory Sensing Based on Mobile Phones in Urban Spaces.- A Slimmer and Deeper Approach to Network Structures for Image Denoising and Dehazing.- PC-OPT: A SfM Point Cloud Denoising Algorithm.- GELAB and Hybrid Optimization Using Grammatical Evolution.- Distribution-wise Symbolic Aggregate approXimation (dwSAX).- Intelligent Call Routing for Telecommunications Call-Centers.-Entropy Based Grey Wolf Optimizer.- Mapping a Clinical Case Description to an Argumentation Framework: a Preliminary Assessment.- Learning User Comfort and Well-being through Smart Devices.- A Deep Learning Approach to Forecast the Influent Flow in Wastewater Treatment Plants.- Automatic Multispectral Image Classification of Plant Virus from Leaf Samples.- Towards the Modeling of the Hot Rolling Industrial Process. Preliminary Results.


Titel: Intelligent Data Engineering and Automated Learning - IDEAL 2020
Untertitel: 21st International Conference, Guimaraes, Portugal, November 4-6, 2020, Proceedings, Part I
EAN: 9783030623623
Digitaler Kopierschutz: Wasserzeichen
Format: E-Book (pdf)
Hersteller: Springer International Publishing
Genre: IT & Internet
Anzahl Seiten: 400
Veröffentlichung: 29.10.2020
Dateigrösse: 50.2 MB

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