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Maintenance of Forest Biodiversity
| Maintenance of Forest Biodiversity |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2023 |
| Descrizione fisica | 1 online resource (258 p.) |
| Soggetto topico |
Biology, life sciences
Ecological science, the Biosphere Research & information: general |
| Soggetto non controllato |
aboveground biomass
acoustic indices altitude arbuscular mycorrhizal fungi beta diversity biodiversity monitoring biogeography biomass allocation birds canonical correlation analysis community assembly competitive exclusion deciduous broad-leaved forests dynamic changes environmental variables forest management functional richness functional trait gap size Godron stability habitat filtering Hainan island influence interspecific association interspecific competition intra- and interspecific interactions intraspecific competition litter decomposition microenvironment mortality process multi-site generalized dissimilarity modeling natural mixed forests natural regeneration net relatedness index niche theory nonstructural carbohydrates novel approach nutrient release object-based image analysis phylogenetic signal plant diversity PLFA analysis precipitation recruitment process regression dominant species replacement richness root system characteristics root-soil-microbial interactions seedling age seedling bank soil available phosphorus soil chemical elements soil chemical property soil depth layer soil microbe soil nutrients soil pH soil water content soundscape ecology spatial distribution spatial structure parameters species diversity spectrograms stand structural characteristic stand structure subtropical evergreen broadleaved forest temperature the Sankey diagram the southern Taihang Mountains tropical monsoonal forest understory vegetation urban forests β-diversity |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911053219303321 |
| MDPI - Multidisciplinary Digital Publishing Institute, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistical Machine Learning for Human Behaviour Analysis
| Statistical Machine Learning for Human Behaviour Analysis |
| Autore | Moeslund Thomas |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (300 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
3D convolutional neural networks
accuracy action recognition adaptive classifiers age classification attention allocation attention behavior biometric recognition blurring detection body movements boundary segmentation categorical data committee of classifiers concept drift context-aware framework convolutional neural network deep learning discrete stationary wavelet transform emotion recognition Empatica E4 ensemble methods face analysis face segmentation false negative rate fibromyalgia fingerprint image enhancement fingerprint quality foggy image frequency domain gait event gender classification gestures hand sign language head pose estimation hybrid entropy individual behavior estimation information entropy interpretable machine learning k-means clustering Kinect sensor Learning Using Concave and Convex Kernels multi-modal multi-objective evolutionary algorithms multimodal-based human identification neural networks noisy image object contour detection privacy privacy-aware profoundly deaf recurrent concepts restricted Boltzmann machine (RBM) rule-based classifiers saliency detection self-reported survey silhouettes difference single pixel single photon image acquisition singular point detection spatial domain spectrograms speech speech emotion recognition statistical-based time-frequency domain and crowd condition stock price direction prediction time-of-flight toe-off detection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557288403321 |
Moeslund Thomas
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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