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Intelligence Science and Big Data Engineering. Big Data and Machine Learning : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang
| Intelligence Science and Big Data Engineering. Big Data and Machine Learning : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang |
| Autore | Cui Zhen |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Springer Nature, 2019 |
| Descrizione fisica | 1 online resource (473 pages) |
| Disciplina |
006.3
006.6 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Artificial intelligence Data mining Computer science Computer Vision Artificial Intelligence Data Mining and Knowledge Discovery Models of Computation |
| ISBN | 3-030-36204-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Analysis of WLAN's Receiving Signal Strength Indication for Indoor Positioning Computational Decomposition of Style for Controllable and Enhanced Style Transfer Laplacian Welsch Regularization for Robust Semi-supervised Dictionary Learning Non-local MMDenseNet with Cross-Band Features for Audio Source Separation A New Method of Metaphor Recognition for A-is-B Model in Chinese Sentences Layerwise Recurrent Autoencoder for Real-World Traffic Flow Forecasting Mining Meta-association Rules for Different Types of Traffic Accidents Reliable Domain Adaptation with Classifiers Competition An End-to-End LSTM-MDN Network for Projectile Trajectory Prediction DeepTF: Accurate Prediction of Transcription Factor Binding Sites by Combining Multi-scale Convolution and Long Short-Term Memory Neural Network Epileptic Seizure Prediction Based on Convolutional Recurrent Neural Network with Multi-Timescale L2R-QA: An Open-Domain Question Answering Framework Attention Relational Network for Few-Shot Learning Syntactic Analysis of Power Grid Emergency Pre-plans Based on Transfer Learning Improved CTC-Attention Based End-to-End Speech Recognition on Air Traffic Control Revisit Lmser from a Deep Learning Perspective A New Network Traffic Identification Base on Deep Factorization Machine 3Q: A 3-Layer Semantic Analysis Model for Question Suite Reduction Data Augmentation for Deep Learning of Judgment Documents An Advanced Least Squares Twin Multi-class Classification Support Vector Machine for Few-Shot Classification LLN-SLAM: A Lightweight Learning Network Semantic SLAM Meta-cluster Based Consensus Clustering with Local Weighting and Random Walking Robust Nonnegative Matrix Factorization Based on Cosine Similarity Induced Metric Intellectual Property in Colombian Museums: An Application of Machine Learning Hybrid Matrix Factorization for Multi-view Clustering Car Sales Prediction Using Gated Recurrent Units Neural Networks with Reinforcement Learning A Multilayer Sparse Representation of Dynamic Brain Functional Network Based on Hypergraph Theory for ADHD Classification Stress Wave Tomography of Wood Internal Defects Based on Deep Learning and Contour Constraint Under Sparse Sampling Robustness of Network Controllability Against Cascading Failure Multi-modality Low-Rank Learning Fused First-Order and Second-Order Information for Computer-Aided Diagnosis of Schizophrenia A Joint Bitrate and Buffer Control Scheme for Low-Latency Live Streaming Causal Discovery of Linear Non-Gaussian Acyclic Model with Small Samples Accelerate Black-Box Attack with White-Box Prior Knowledge A Dynamic Model + BFR Algorithm for Streaming Data Sorting Smartphone Behavior Based Electronical Scale Validity Assessment Framework Discrimination Model of QAR High-Severity Events Using Machine Learning A New Method of Improving BERT for Text Classification |
| Record Nr. | UNINA-9910357840503321 |
| Cui Zhen | ||
| Springer Nature, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligence Science and Big Data Engineering. Big Data and Machine Learning [[electronic resource] ] : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang
| Intelligence Science and Big Data Engineering. Big Data and Machine Learning [[electronic resource] ] : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (473 pages) |
| Disciplina | 006.3 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Data mining Computers Image Processing and Computer Vision Artificial Intelligence Data Mining and Knowledge Discovery Models and Principles |
| ISBN | 3-030-36204-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466184703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Intelligence Science and Big Data Engineering. Visual Data Engineering [[electronic resource] ] : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part I / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang
| Intelligence Science and Big Data Engineering. Visual Data Engineering [[electronic resource] ] : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part I / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (594 pages) |
| Disciplina | 006.31 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Data mining Computers Image Processing and Computer Vision Artificial Intelligence Data Mining and Knowledge Discovery Models and Principles |
| ISBN | 3-030-36189-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466281003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Intelligence Science and Big Data Engineering. Visual Data Engineering : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part I / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang
| Intelligence Science and Big Data Engineering. Visual Data Engineering : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part I / / edited by Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (594 pages) |
| Disciplina |
006.31
006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Artificial intelligence Data mining Computer science Computer Vision Artificial Intelligence Data Mining and Knowledge Discovery Models of Computation |
| ISBN | 3-030-36189-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910357840703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||