Effetto di tensioattivi su alcune specie vegetali : nota 3 : esperienza in campo su patate (Solanum tuberosum) / Ada Luzzati

• Record Nr.: UNINA990001771460403321
• Autore: Luzzati, Ada
• Pubbl/distr/stampa: Chieri : [s.e.], 1974
• Descrizione fisica: p. 112-122 ; 24 cm
• Disciplina: 581.13
• Locazione: FAGBC
• Collocazione: 60 OP. 93/13
• Lingua di pubblicazione: Italiano
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Estr. da: Bollettino dei Laboratori Chimici Provinciali, 25(1974), n. 6.

Activity learning : discovering, recognizing, and predicting human behavior from sensor data / / Diane J. Cook, Narayanan C. Krishnan

• Record Nr.: UNINA9910813786103321
• Autore: Cook Diane J. <1963->
• Pubbl/distr/stampa: Hoboken, New Jersey : , : John Wiley & Sons, Inc., , 2015; ©2015
• ISBN: 1-119-01025-X; 1-119-01023-3; 1-119-01024-1
• Descrizione fisica: 1 online resource (282 p.)
• Collana: Wiley Series on Parallel and Distributed Computing
• Classificazione: TEC008060TEC064000COM021030
• Disciplina: 371.3
• Soggetti: Active learning - Data processing; Detectors - Data processing; Multisensor data fusion
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Machine generated contents note: 1 Introduction 2 Activities 2.1 Definitions 2.2 Classes of Activities 2.3 Additional Reading 3 Sensing 3.1 Sensors Used for Activity Learning 3.2 Sample Sensor Datasets 3.3 Features 3.4 Multisensor Fusion 3.5 Additional Reading 4 Machine Learning 4.1 Supervised Learning Framework 4.2 Na&iuml;ve Bayes Classifier 4.3 Gaussian Mixture Model 4.4 Hidden Markov Model 4.5 Decision Tree 4.6 Support Vector Machine 4.7 Conditional Random Field 4.8 Combining Classifier Models 4.9 Dimensionality Reduction 4.10 Additional Reading 5 Activity Recognition 5.1 Activity Segmentation 5.2 Sliding Windows 5.3 Unsupervised Segmentation 5.4 Measuring Performance 5.5 Additional Reading 6 Activity Discovery 6.1 Zero-Shot Learning 6.2 Sequence Mining 6.3 Clustering 6.4 Topic Models 6.5 Measuring Performance 6.6 Additional Reading 7 Activity Prediction 7.1 Activity Sequence Prediction 7.2 Activity Forecasting 7.3 Probabilistic Graph-Based Activity Prediction 7.4 Rule-Based Activity Timing Prediction 7.5 Measuring Performance 7.6 Additional Reading 8 Activity Learning in the Wild 8.1 Collecting Annotated Sensor Data 8.2 Transfer Learning 8.3 Multi-Label Learning 8.4 Activity Learning for Multiple Individuals 8.5 Additional Reading 9 Applications of Activity Learning 9.1 Health 9.2 Activity-Aware Services 9.3 Security and Emergency Management 9.4 Activity Reconstruction, Expression and Visualization 9.5 Analyzing Human Dynamics 9.6 Additional Reading 10 The Future of Activity Learning Appendix: Sample Activity Data Bibliography.
• Sommario/riassunto: "The book provides an in-depth look at computational approaches to activity learning from sensor data"--