Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Artificial Neural Networks for IoT-Enabled Smart Applications
| Artificial Neural Networks for IoT-Enabled Smart Applications |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2023 |
| Descrizione fisica | 1 online resource (268 p.) |
| Soggetto topico |
Medicine and Nursing
Neurosciences |
| Soggetto non controllato |
"dry" immersion
5G and beyond accelerometry ANN arrhythmia artificial intelligence (AI) bark detection biochemical and hematological biomarkers canine activity recognition cardiac chemical carcinogens child drowning prevention communication technologies convolution neural network convolutional neural network COVID-19 decentralized deep learning deep learning neural network distracted driving edge computing Electrocardiogram (ECG) electroencephalography ensemble learning fast forward neural network feature selection method gait hybrid neural network imaginary speech inertial measurement unit Internet of Medical Things IoT Kara One database LogNNet neural network machine learning machine learning sensors microprocessor n/a network slicing architecture Parkinson's disease point clouds remote sensing routine blood values search and rescue system signal processing smartphone stacking systematic literature review (SLR) TUG test water level prediction wearable computing |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911053081103321 |
| MDPI - Multidisciplinary Digital Publishing Institute, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Science and Knowledge Discovery
| Data Science and Knowledge Discovery |
| Autore | Portela Filipe |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (254 p.) |
| Soggetto topico |
Computer science
Information technology industries |
| Soggetto non controllato |
activity recognition
adaptation process ArcGIS artificial intelligence attribution authorship automation big data Big Data box-counting framework chatbots classification content base image retrieval COVID-19 crisis reporting customer relationship management (CRM) dashboard data analysis data analytics data augmentation data mining data science databases decision systems deep features deep learning digital humanities digital infrastructures distracted driving driving behavior driving operation area e-commerce economic determinants of open data ESP32 microcontroller feature extraction forensic intelligence fractal dimension geoinformation technology governance and social institutions humanities ICT information systems interdisciplinary research internet of things ioCOVID19 journalists linked open data LoRaWAN machine learning media analytics media criticism multimedia document retrieval n/a neural networks news media open government data prediction by partial matching public health rough sets rule based systems SARS-CoV-2 script Python semantic information retrieval smart homes social sciences spatio-temporal territorial road network text mining textbook research The Things Network Web Intelligence WebGIS |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576878103321 |
Portela Filipe
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||