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Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments
| Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| Autore | Woźniak Marcin |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (454 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
3D convolutional neural networks
3D imaging activity measure advanced driver assistance system (ADAS) anchor box artefacts artificial bee colony atrous convolution augmented reality automatic design benchmark bio-inspired techniques brain hemorrhage cascade classifier cascaded center-ness citrus CNN complex search request computer vision continuous casting convolution neural networks (CNNs) convolutional neural network convolutional neural networks cross-scale CT brain CT images data acquisition deep learning deep sort defect detection deformable localization drone detection evidence chains evolving connectionist systems fabric defect feature extraction feature fusion few shot learning focal loss generative adversarial network grow-when-required neural network hand gesture recognition hepatic cancer high-speed trains human-robot interaction Hungarian algorithm hunting image analysis image processing image recognition industrial environments information retriever sensor InSAR machine learning marine systems mixed kernels multi-hop reasoning multi-scale multi-sensor fusion n/a nearest neighbor filtering neural network non-stationary object detection object detector object tracking one-class classifier optical flows parameter efficiency pests and diseases identification pixel convolution pose estimation reinforcement learning RFI semantic segmentation ship classification ship radiated noise spatial pooling spatiotemporal interest points sports scene superalloy tool surface defects surface electromyography (sEMG) SVM synthetic images three-dimensional (3D) vision thresholding tool wear monitoring Traffic sign detection and tracking (TSDR) UAV detection UAV imagery underwater acoustics unmanned aerial vehicles vehicle detection vehicular traffic congestion vehicular traffic flow classification vehicular traffic flow detection video classification video surveillance visual detection visual inspection visual question answering Yolo YOLOv2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557360703321 |
Woźniak Marcin
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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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Remote Sensing in Agriculture: State-of-the-Art
| Remote Sensing in Agriculture: State-of-the-Art |
| Autore | Borgogno-Mondino Enrico |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (220 p.) |
| Soggetto topico |
Environmental science, engineering and technology
History of engineering and technology Technology: general issues |
| Soggetto non controllato |
alpha angle
anisotropy apple orchard damage biomass CDL corn crop height crop management crop Monitoring crop water stress monitoring crop yield prediction cross-scale data blending digital number (DN) DJI Phantom 4 Multispectral (P4M) economic loss entropy feature selection field phenotyping gap-filling Hidden Markov Random Field HMRF hyperspectral imaging insurance support Landsat lodging MODIS northern Mongolia oasis crop type mapping Parrot Sequoia (Sequoia) plant disease detection polarimetric decomposition precision agriculture (PA) random forest (RF) recursive feature increment (RFI) red-edge spectral bands and indices reflectance remote sensing (RS) remote sensing indices SAR Sentinel-1 Sentinel-1 and 2 integration soil moisture Karnataka India soil moisture semi-empirical model soybean spatial resolution spectral angle mapper spring wheat statistically homogeneous pixels (SHPs) storm damage mapping support vector machine support vector regression Synthetic Aperture Radar synthetic aperture radar (SAR) thermal infrared (TIR) thermal UAV RS UAV UAV-based LiDAR unmanned aerial vehicles (UAVs) vegetation index (VI) vegetation status monitoring volumetric soil moisture winter wheat yellow rust yield estimation |
| ISBN | 3-0365-5484-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Remote Sensing in Agriculture |
| Record Nr. | UNINA-9910637779903321 |
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Borgogno-Mondino Enrico
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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