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Geoinformatics in Citizen Science
| Geoinformatics in Citizen Science |
| Autore | Bordogna Gloria |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (206 p.) |
| Soggetto non controllato |
education
geoinformatics GIS education classification accuracy latent class analysis location-based social networks (LBSNs) geoinformation in citizen science toponym recruitment community mapping user preference land administration systems positional accuracy sample size spatial proximity crowdsourced geoinformation collection and analysis air quality estimation digital cartography crowdsourcing VGI in citizen science crowdsourced data collection social relationship effect analysis GIS data quality opportunistic data volunteer volunteered geographic information (VGI) VGI data fusion algorithms OpenStreetMap volunteer geographic information citizen science ensemble spatial bias projects survey Alaska marine mammal brown marmorated stink bug social media Environmental niche modeling data analysis Pentatomidae QGIS MaxEnt spatial accuracy clustering air pollution data import sky images |
| ISBN | 3-03921-073-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346690703321 |
Bordogna Gloria
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information Bottleneck : Theory and Applications in Deep Learning
| Information Bottleneck : Theory and Applications in Deep Learning |
| Autore | Geiger Bernhard |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (274 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
information theory
variational inference machine learning learnability information bottleneck representation learning conspicuous subset stochastic neural networks mutual information neural networks information bottleneck compression classification optimization classifier decision tree ensemble deep neural networks regularization methods information bottleneck principle deep networks semi-supervised classification latent space representation hand crafted priors learnable priors regularization deep learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Information Bottleneck |
| Record Nr. | UNINA-9910557582803321 |
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Geiger Bernhard
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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