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Artificial Neural Networks and Evolutionary Computation in Remote Sensing
| Artificial Neural Networks and Evolutionary Computation in Remote Sensing |
| Autore | Kavzoglu Taskin |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (256 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
convolutional neural network
image segmentation multi-scale feature fusion semantic features Gaofen 6 aerial images land-use Tai’an convolutional neural networks (CNNs) feature fusion ship detection optical remote sensing images end-to-end detection transfer learning remote sensing single shot multi-box detector (SSD) You Look Only Once-v3 (YOLO-v3) Faster RCNN statistical features Gaofen-2 imagery winter wheat post-processing spatial distribution Feicheng China light detection and ranging LiDAR deep learning convolutional neural networks CNNs mask regional-convolutional neural networks mask R-CNN digital terrain analysis resource extraction hyperspectral image classification few-shot learning quadruplet loss dense network dilated convolutional network artificial neural networks classification superstructure optimization mixed-inter nonlinear programming hyperspectral images super-resolution SRGAN model generalization image downscaling mixed forest multi-label segmentation semantic segmentation unmanned aerial vehicles classification ensemble machine learning Sentinel-2 geographic information system (GIS) earth observation on-board microsat mission nanosat AI on the edge CNN |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557148403321 |
Kavzoglu Taskin
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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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Image and Video Processing and Recognition Based on Artificial Intelligence
| Image and Video Processing and Recognition Based on Artificial Intelligence |
| Autore | Park Kang Ryoung |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (431 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
emotion recognition
brain computer interface bag of deep features continuous wavelet transform face image analysis deep learning face parsing facial attributes classification building extraction convolutional neural networks mask R-CNN high-resolution remote sensing image autoencoders semi-supervised learning computer vision pathology epidermis skin image processing generative models generative adversarial net depth map super-resolution guidance residual network channel interaction pose estimation body orientation multi-person multi-task surface defect detection active learning generative adversarial network presentation attack detection artificial image generation presentation attack face images ultrasound image malignant thyroid nodule artificial intelligence weighted binary cross-entropy loss infrared circumferential scanning system target recognition deep convolutional neural networks data augmentation transfer learning bounding box regression loss function medical image fusion convolutional neural network image pyramid multi-scale decomposition armature surface inspection action recognition social robotics common spatial patterns vehicle recognition multi resolution network optimization semantic segmentation global context local context fully convolutional networks image-to-image conversion image de-raining label to photos edges to photos generative adversarial network (GAN) remote sensing helicopter footage crowd counting multitask learning normalized cross-correlation Marr wavelets entropy and response graph matching RANSAC GC–LSTM model typhoon satellite image prediction system monocular depth estimation feature distillation joint attention finger-vein recognition camera position finger position lighting unobserved database heterogeneous database domain adaptation cycle-consistent adversarial networks SDUMLA-HMT-DB HKPolyU-DB biometrics face recognition single-sample face recognition binarized statistical image features K-nearest neighbors sparse coding fast approximation homotopy iterative hard thresholding object recognition character recognition orthogonal polynomials orthogonal moments Krawtchouk polynomials Tchebichef polynomials support vector machine |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557371203321 |
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Park Kang Ryoung
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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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Precision Poultry Farming
| Precision Poultry Farming |
| Autore | Zhao Yang |
| Pubbl/distr/stampa | Basel, : MDPI Books, 2022 |
| Descrizione fisica | 1 electronic resource (176 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Animals & society |
| Soggetto non controllato |
broiler
activity index time interval age image processing poultry cage-free preening behavior mask R-CNN residual network broiler chicken machine vision image restoring precision poultry farming feeding system pecking force precision livestock farming poultry farming information management cloud database disease detection acoustic audio frequency behavior image analysis animal welfare movement analysis LED comfort index manure area manure coverage proportion environment control ammonia emission layer house laying hen daily behavior machine learning inertia sensor walking ability animal behavior precision livestock PLF precise feeding ideal protein animal health immune system productive parameters management |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595076003321 |
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Zhao Yang
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| Basel, : MDPI Books, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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