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.
Machine Learning in Sensors and Imaging
| Machine Learning in Sensors and Imaging |
| Autore | Nam Hyoungsik |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (302 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
activity recognition
artificial neural network BLDC BP artificial neural network burr formation capacitive chaotic system color prior model compressive sensing computer vision coniferous plantations convex optimization convolutional neural network cut interruption deep learning display electric machine protection explainable artificial intelligence extrinsic camera calibration fiber laser forest growing stem volume fuzzy image classification image denoising image encryption imbalanced activities intelligent vehicles laser cutting machine learning machine learning-based classification marine maximum likelihood estimation mixed Poisson-Gaussian likelihood modulation transfer function Naïve bayes neural network noisy non-uniform foundation object detection obstacle avoidance on-shelf availability path planning piston error detection plaintext related plankton Q-learning quality monitoring random forest real-world red-edge band reinforcement learning risk assessment robot arm sampling methods segmented telescope semi-supervised semi-supervised learning SNR star image stochastic analysis structure from motion stylus target reaching temperature estimation texture feature touchscreen transmission-line corridors variable selection vehicle-pavement-foundation interaction wearable sensors wildfire YOLO algorithm |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566484703321 |
Nam Hyoungsik
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sensors in Agriculture: Volume 1 / Dimitrios Moshou
| Sensors in Agriculture: Volume 1 / Dimitrios Moshou |
| Autore | Moshou Dimitrios |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (346 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
optical sensor
spectral analysis response surface sampling sensor evaluation electromagnetic induction multivariate water quality parameters mandarin orange crop inspection platform SPA-MLR object tracking feature selection simultaneous measurement diseases genetic algorithms processing of sensed data electrochemical sensors thermal image ECa-directed soil sampling handheld recognition patterns salt concentration clover-grass bovine embedded hardware weed control soil field crops vineyard connected dominating set water depth sensors SS-OCT wheat striped stem-borer silage geostatistics detection NIR hyperspectral imaging electronic nose machine learning virtual organizations of agents packing density data validation and calibration dataset Wi-SUN temperature sensors geoinformatics gas sensor X-ray fluorescence spectroscopy vegetable oil photograph-grid method Vitis vinifera WSN distribution algorithms laser-induced breakdown spectroscopy irrigation quality assessment energy efficiency wireless sensor network (WSN) geo-information Fusarium texture features weeds discrimination big data soil moisture sensors meat spoilage land cover stereo imaging near infrared sensors biological sensing compound sensor pest management moisture plant localization heavy metal contamination artificial neural networks spectral pre-processing moisture content apparent soil electrical conductivity data fusion semi-arid regions smart irrigation back propagation model wireless sensor network energy balance light-beam fluorescent measurement agriculture precision agriculture deep learning spectroscopy hulled barely dielectric probe RPAS water supply network rice leaves mobile app gradient boosted machines hyperspectral camera one-class nitrogen LiDAR total carbon chemometrics analysis rice agricultural land on-line vis-NIR measurement CARS obstacle detection stratification neural networks regression estimator Kinect proximity sensing distributed systems pest noninvasive detection texture feature soil mapping classification soil salinity visible and near-infrared reflectance spectroscopy germination computer vision hyperspectral imaging diffusion dielectric dispersion UAS random forests case studies total nitrogen thermal imaging cameras dry matter composition near-infrared salt tolerance deep convolutional neural networks soil type classification water management preprocessing methods wireless sensor networks (WSN) remote sensing image classification precision plant protection radar spatial variability GF-1 satellite plant disease naked barley leaf area index CIE-Lab change of support radiative transfer model 3D reconstruction plant phenotyping vine near infrared vegetation indices remote sensing greenhouse time-series data scattering sensor crop area speckle spatial data grapevine breeding wide field view partial least squares-discriminant analysis spiking area frame sampling chromium content machine-learning RGB-D sensor pest scouting PLS Capsicum annuum spatial-temporal model drying temperature boron tolerance ambient intelligence laser wavelength fuzzy logic dynamic weight landslide management zones real-time processing event detection crop monitoring apple shelf-life rice field monitoring wireless sensor birth sensor proximal sensor |
| ISBN |
9783038974130
3038974137 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346859003321 |
|
Moshou Dimitrios
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sensors in Agriculture: Volume 2 / Dimitrios Moshou
| Sensors in Agriculture: Volume 2 / Dimitrios Moshou |
| Autore | Moshou Dimitrios |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (354 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
optical sensor
spectral analysis response surface sampling sensor evaluation electromagnetic induction multivariate water quality parameters mandarin orange crop inspection platform SPA-MLR object tracking feature selection simultaneous measurement diseases genetic algorithms processing of sensed data electrochemical sensors thermal image ECa-directed soil sampling handheld recognition patterns salt concentration clover-grass bovine embedded hardware weed control soil field crops vineyard connected dominating set water depth sensors SS-OCT wheat striped stem-borer silage geostatistics detection NIR hyperspectral imaging electronic nose machine learning virtual organizations of agents packing density data validation and calibration dataset Wi-SUN temperature sensors geoinformatics gas sensor X-ray fluorescence spectroscopy vegetable oil photograph-grid method Vitis vinifera WSN distribution algorithms laser-induced breakdown spectroscopy irrigation quality assessment energy efficiency wireless sensor network (WSN) geo-information Fusarium texture features weeds discrimination big data soil moisture sensors meat spoilage land cover stereo imaging near infrared sensors biological sensing compound sensor pest management moisture plant localization heavy metal contamination artificial neural networks spectral pre-processing moisture content apparent soil electrical conductivity data fusion semi-arid regions smart irrigation back propagation model wireless sensor network energy balance light-beam fluorescent measurement agriculture precision agriculture deep learning spectroscopy hulled barely dielectric probe RPAS water supply network rice leaves mobile app gradient boosted machines hyperspectral camera one-class nitrogen LiDAR total carbon chemometrics analysis rice agricultural land on-line vis-NIR measurement CARS obstacle detection stratification neural networks regression estimator Kinect proximity sensing distributed systems pest noninvasive detection texture feature soil mapping classification soil salinity visible and near-infrared reflectance spectroscopy germination computer vision hyperspectral imaging diffusion dielectric dispersion UAS random forests case studies total nitrogen thermal imaging cameras dry matter composition near-infrared salt tolerance deep convolutional neural networks soil type classification water management preprocessing methods wireless sensor networks (WSN) remote sensing image classification precision plant protection radar spatial variability GF-1 satellite plant disease naked barley leaf area index CIE-Lab change of support radiative transfer model 3D reconstruction plant phenotyping vine near infrared vegetation indices remote sensing greenhouse time-series data scattering sensor crop area speckle spatial data grapevine breeding wide field view partial least squares-discriminant analysis spiking area frame sampling chromium content machine-learning RGB-D sensor pest scouting PLS Capsicum annuum spatial-temporal model drying temperature boron tolerance ambient intelligence laser wavelength fuzzy logic dynamic weight landslide management zones real-time processing event detection crop monitoring apple shelf-life rice field monitoring wireless sensor birth sensor proximal sensor |
| ISBN |
9783038977452
3038977454 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346858903321 |
|
Moshou Dimitrios
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||