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Advanced Sensing and Control for Connected and Automated Vehicles
| Advanced Sensing and Control for Connected and Automated Vehicles |
| Autore | Huang Chao |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (284 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
analytic hierarchy architecture
articulated cargo trucks artificial neural networks attention attention feature fusion autonomous driving autonomous vehicle autonomous vehicles collision warning system connected and autonomous vehicles data-driven dead reckoning electric vehicle electroencephalogram end-to-end learning executive control fronto-parietal network in-vehicle network kabsch algorithm kalman filter model predictive control multi-scale channel attention multi-task learning multiple-model n/a object detection object vehicle estimation off-tracking path planning potential field radar accuracy radar latency real-time control roll stability sigmoid curve simulated driving simulation string stability task-cuing experiment time to collision traffic scenes trajectory tracking TROOP truck platooning tyre blow-out ultra-wideband unified chassis control Unscented Kalman Filter unsprung mass urban platooning urban vehicle platooning V2V communication vehicle dynamic parameters vehicle dynamics model vehicle-to-vehicle communication weighted interpolation yaw stability |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566481403321 |
Huang Chao
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep Learning for Facial Informatics
| Deep Learning for Facial Informatics |
| Autore | Hsu Gee-Sern Jison |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (102 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
2D attribute maps
3D geometry data age estimation coarse-to-fine convolutional neural network convolutional neural network (CNN) convolutional neural networks deep learning deep metric learning depth emotion classification external knowledge face liveness detection facial images processing facial key point detection facial landmarking fused CNN feature generative adversarial network image classification merging networks multi-task learning RGB thermal image |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557721303321 |
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Hsu Gee-Sern Jison
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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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Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (414 pages) |
| Soggetto topico | Computer science |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN |
9783038976851
3038976857 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755603321 |
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Wang Qi
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (363 pages) |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN |
9783038976998
3038976997 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755503321 |
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Wang Qi
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Lifelong machine learning / / Zhiyuan Chen, Bing Liu
| Lifelong machine learning / / Zhiyuan Chen, Bing Liu |
| Autore | Chen Zhiyuan (Computer scientist) |
| Pubbl/distr/stampa | [San Rafael, California] : , : Morgan & Claypool, , 2017 |
| Descrizione fisica | 1 online resource (147 pages) : illustrations (some color) |
| Disciplina | 006.31 |
| Collana | Synthesis lectures on artificial intelligence and machine learning |
| Soggetto topico | Machine learning |
| Soggetto non controllato |
lifelong machine learning
lifelong learning; learning with memory cumulative learning multi-task learning transfer learning |
| ISBN | 1-62705-877-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
1. Introduction -- 1.1 A brief history of lifelong learning -- 1.2 Definition of lifelong learning -- 1.3 Lifelong learning system architecture -- 1.4 Evaluation methodology -- 1.5 Role of big data in lifelong learning -- 1.6 Outline of the book --
2. Related learning paradigms -- 2.1 Transfer learning -- 2.1.1 Structural correspondence learning -- 2.1.2 Naïve Bayes transfer classifier -- 2.1.3 Deep learning in transfer learning -- 2.1.4 Difference from lifelong learning -- 2.2 Multi-task learning -- 2.2.1 Task relatedness in multi-task learning -- 2.2.2 GO-MTL: multi-task learning using latent basis -- 2.2.3 Deep learning in multi-task learning -- 2.2.4 Difference from lifelong learning -- 2.3 Online learning -- 2.3.1 Difference from lifelong learning -- 2.4 Reinforcement learning -- 2.4.1 Difference from lifelong learning -- 2.5 Summary -- 3. Lifelong supervised learning -- 3.1 Definition and overview -- 3.2 Lifelong memory-based learning -- 3.2.1 Two memory-based learning methods -- 3.2.2 Learning a new representation for lifelong learning -- 3.3 Lifelong neural networks -- 3.3.1 MTL Net -- 3.3.2 Lifelong EBNN -- 3.4 Cumulative learning and self-motivated learning -- 3.4.1 Training a cumulative learning model -- 3.4.2 Testing a cumulative learning model -- 3.4.3 Open world learning for unseen class detection -- 3.5 ELLA: an efficient lifelong learning algorithm -- 3.5.1 Problem setting -- 3.5.2 Objective function -- 3.5.3 Dealing with the first inefficiency -- 3.5.4 Dealing with the second inefficiency -- 3.5.5 Active task selection -- 3.6 LSC: lifelong sentiment classification -- 3.6.1 Naïve Bayesian text classification -- 3.6.2 Basic ideas of LSC -- 3.6.3 LSC technique -- 3.7 Summary and evaluation datasets -- 4. Lifelong unsupervised learning -- 4.1 Lifelong topic modeling -- 4.2 LTM: a lifelong topic model -- 4.2.1 LTM model -- 4.2.2 Topic knowledge mining -- 4.2.3 Incorporating past knowledge -- 4.2.4 Conditional distribution of Gibbs sampler -- 4.3 AMC: a lifelong topic model for small data -- 4.3.1 Overall algorithm of AMC -- 4.3.2 Mining must-link knowledge -- 4.3.3 Mining cannot-link knowledge -- 4.3.4 Extended Pólya Urn model -- 4.3.5 Sampling distributions in Gibbs sampler -- 4.4 Lifelong information extraction -- 4.4.1 Lifelong learning through recommendation -- 4.4.2 AER algorithm -- 4.4.3 Knowledge learning -- 4.4.4 Recommendation using past knowledge -- 4.5 Lifelong-RL: lifelong relaxation labeling -- 4.5.1 Relaxation labeling -- 4.5.2 Lifelong relaxation labeling -- 4.6 Summary and evaluation datasets -- 5. Lifelong semi-supervised learning for information extraction -- 5.1 NELL: a never ending language learner -- 5.2 NELL architecture -- 5.3 Extractors and learning in NELL -- 5.4 Coupling constraints in NELL -- 5.5 Summary -- 6. Lifelong reinforcement learning -- 6.1 Lifelong reinforcement learning through multiple environments -- 6.1.1 Acquiring and incorporating bias -- 6.2 Hierarchical Bayesian lifelong reinforcement learning -- 6.2.1 Motivation -- 6.2.2 Hierarchical Bayesian approach -- 6.2.3 MTRL algorithm -- 6.2.4 Updating hierarchical model parameters -- 6.2.5 Sampling an MDP -- 6.3 PG-ELLA: lifelong policy gradient reinforcement learning -- 6.3.1 Policy gradient reinforcement learning -- 6.3.2 Policy gradient lifelong learning setting -- 6.3.3 Objective function and optimization -- 6.3.4 Safe policy search for lifelong learning -- 6.3.5 Cross-domain lifelong reinforcement learning -- 6.4 Summary and evaluation datasets -- 7. Conclusion and future directions -- Bibliography -- Authors' biographies. |
| Record Nr. | UNINA-9910151959503321 |
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Chen Zhiyuan (Computer scientist)
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| [San Rafael, California] : , : Morgan & Claypool, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Molecular Psychiatry
| Molecular Psychiatry |
| Autore | Rein Theo |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (288 p.) |
| Soggetto topico |
Medicine and Nursing
Mental health services |
| Soggetto non controllato |
(2R,6R)-Hydroxynorketamine
5-HT 4 receptor 5-HT4R acid sphingomyelinase actin dynamics affective temperament alcohol dependence alpha-synuclein Alzheimer's disease antidepressant antidepressant treatment antidepressants antipsychotics basic-helix-loop-helix BDNF behavior biomarker discovery biomarkers bipolar disorder brain cardiovascular disease cell adhesion molecules chemokines childhood-onset schizophrenia (COS) circadian rhythms coactivator cognition copy number variation (CNV) cordance CRMP-2 CyP40 cytoskeleton dendritic arborization depression DISC1 DNA methylation dopaminergic gene polymorphisms DRR1 drug design early neurodevelopment electroconvulsive therapy endocrinology expression FAM107A FKBP5 FKBP51 FKBP52 forced swimming gender gene expression general cognitive function genetic correlation glucocorticoids GR GWAS Hamilton Scale of Depression hippocampus HPA axis Hsp90 Immune response immunohistochemistry immunology induced pluripotent stem cell (iPSC) inflammation intelligence Ketamine liver enzymes machine learning major depression major depressive disorder mineralocorticoid receptor knockout miRNAs molecular chaperones mood disorder multi-target drugs multi-task learning n/a nervous system neurodevelopment neuroinflammation neuronal differentiation obesity Parkinson's disease polypharmacology PP5 PPARγ proteomics PSA-NCAM psychiatric disease psychiatry rapid-acting resilience response variability Roman rat lines schizophrenia serotonin sex difference sleep sleep EEG SNCA social defeat sphingolipid metabolism steroid hormones stress stress physiology stress response susceptibility synapse T cells Th17 cells transcription biology Treg cells trkB TU3A western blot withdrawal |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557793503321 |
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Rein Theo
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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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