000			08634nam a22006855i 4500
001			978-3-030-86365-4
003			DE-He213
005			20241121084603.0
007			cr nn 008mamaa
008			210910s2021 sz | s |||| 0|eng d
020			_a9783030863654 _9978-3-030-86365-4
024	7		_a10.1007/978-3-030-86365-4 _2doi
041			_aeng
050		4	_aQ334-342
050		4	_aTA347.A78
072		7	_aUYQ _2bicssc
072		7	_aCOM004000 _2bisacsh
072		7	_aUYQ _2thema
245	1	0	_aArtificial Neural Networks and Machine Learning – ICANN 2021 _h[electronic resource] : _b30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14–17, 2021, Proceedings, Part III / _cedited by Igor Farkaš, Paolo Masulli, Sebastian Otte, Stefan Wermter.
250			_a1st ed. 2021.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021.
300			_aXXIV, 697 p. 220 illus., 204 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aTheoretical Computer Science and General Issues, _x2512-2029 ; _v12893
505	0		_aGenerative neural networks -- Binding and Perspective Taking as Inference in a Generative Neural Network Model -- Advances in Password Recovery using Generative Deep Learning Techniques -- o 0886 - Dilated Residual Aggregation Network for Text-guided Image Manipulation -- Denoising AutoEncoder based Delete and Generate Approach for Text Style Transfer -- GUIS2Code: A Computer Vision Tool to Generate Code Automatically from Graphical User Interface Sketches -- Generating Math Word Problems from Equations with Topic Consistency Maintaining and Commonsense Enforcement -- Generative properties of Universal Bidirectional Activation-based Learning -- Graph neural networks I -- Joint Graph Contextualized Network for Sequential Recommendation -- Relevance-Aware Q-matrix Calibration for Knowledge Tracing -- LGACN: A Light Graph Adaptive Convolution Network for Collaborative Filtering -- HawkEye: Cross-Platform Malware Detection with Representation Learning on Graphs -- An Empirical Study of the Expressiveness of Graph Kernels and Graph Neural Networks -- Multi-resolution Graph Neural Networks for PDE approximation -- Link Prediction on Knowledge Graph by Rotation Embedding on the Hyperplane in the Complex Vector Space -- Graph neural networks II -- Contextualise Entities and Relations: An Interaction Method for Knowledge Graph Completion -- Civil Unrest Event Forecasting Using Graphical and Sequential Neural Networks -- Parameterized Hypercomplex Graph Neural Networks for Graph Classification -- Feature Interaction Based Graph Convolutional Networks For Image-text Retrieval -- Generalizing Message Passing Neural Networks to Heterophily using Position Information -- Local and Non-local Context Graph Convolutional Networks for Skeleton-based Action Recognition.-STGATP: A Spatio-temporal Graph Attention Network for Long-term Traffic Prediction -- Hierarchical and ensemble models -- Integrating N-Gram Features into Pre-Trained Model: A Novel Ensemble Model for Multi-Target Stance Detection -- Hierarchical Ensemble for Multi-view Clustering -- Structure-Aware Multi-Scale Hierarchical Graph Convolutional Network for Skeleton Action Recognition -- Learning Hierarchical Reasoning for Text-based Visual Question Answering -- Hierarchical Deep Gaussian Processes Latent Variable Model via Expectation Propagation -- Adaptive Consensus-Based Ensemble for Improved Deep Learning Inference Cost -- Human pose estimation -- Multi-Branch Network for Small Human Pose Estimation -- PNO: Personalized Network Optimization for Human Pose and Shape Reconstruction -- JointPose: Jointly Optimizing Evolutionary Data Augmentation and Prediction Neural Network for 3D Human Pose Estimation -- DeepRehab: Real Time Pose Estimation on the Edge for Knee Injury Rehabilitation -- Image processing -- Subspace constraint for Single Image Super-Resolution -- Towards Fine-Grained Control over Latent Space for Unpaired Image-to-Image Translation -- FMSNet: Underwater Image Restoration by Learning from a Synthesized Dataset -- Towards Measuring Bias in Image Classification -- Towards Image Retrieval with Noisy Labels via Non-deterministic Features -- Image segmentation -- Improving Visual Question Answering by Semantic Segmentation -- Weakly Supervised Semantic Segmentation with Patch-Based Metric Learning Enhancement -- ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation -- Depth Mapping Hybrid Deep Learning Method for Optic Disc and Cup Segmentation on Stereoscopic Ocular Fundus -- RATS: Robust Automated Tracking and Segmentation of Similar Instances -- Knowledge distillation -- Data Diversification Revisited: Why Does It Work? -- A Generalized Meta-Loss Function for Distillation Based Learning Using Privileged Information for Classification and Regression -- Empirical Study of Data-Free Iterative Knowledge Distillation -- Adversarial Variational Knowledge Distillation -- Extract then Distill: Efficient and Effective Task-Agnostic BERT Distillation -- Medical image processing -- Semi-supervised Learning based Right Ventricle Segmentation Using Deep Convolutional Boltzmann Machine Shape Model -- Improved U-Net for Plaque Segmentation of Intracoronary Optical Coherence Tomography Images -- Approximated Masked Global Context Network for Skin Lesion Segmentation -- DSNet: Dynamic Selection Network for Biomedical Image Segmentation -- Computational Approach to Identifying Contrast-Driven Retinal Ganglion Cells -- Radiological Identification of Hip Joint Centers from X-ray Images Using Fast Deep Stacked Network and Dynamic Registration Graph -- A Two-Branch Neural Network for Non-Small-Cell Lung Cancer Classification and Segmentation -- Uncertainty Quantification and Estimation in Medical Image Classification -- Labeling Chest X-Ray Reports Using Deep Learning.
520			_aThe proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as generative neural networks, graph neural networks, hierarchical and ensemble models, human pose estimation, image processing, image segmentation, knowledge distillation, and medical image processing. *The conference was held online 2021 due to the COVID-19 pandemic.
650		0	_aArtificial intelligence.
650		0	_aComputer vision. _92455
650		0	_aApplication software. _94694
650		0	_aEducation _xData processing. _985469
650		0	_aPattern recognition systems. _91133
650		0	_aComputer engineering. _92665
650		0	_aComputer networks . _9968
650	1	4	_aArtificial Intelligence.
650	2	4	_aComputer Vision. _92455
650	2	4	_aComputer and Information Systems Applications.
650	2	4	_aComputers and Education.
650	2	4	_aAutomated Pattern Recognition.
650	2	4	_aComputer Engineering and Networks.
700	1		_aFarkaš, Igor. _eeditor. _0(orcid)0000-0003-3503-2080 _1https://orcid.org/0000-0003-3503-2080 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aMasulli, Paolo. _eeditor. _0(orcid)0000-0002-1389-3894 _1https://orcid.org/0000-0002-1389-3894 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aOtte, Sebastian. _eeditor. _0(orcid)0000-0002-0305-0463 _1https://orcid.org/0000-0002-0305-0463 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aWermter, Stefan. _eeditor. _0(orcid)0000-0003-1343-4775 _1https://orcid.org/0000-0003-1343-4775 _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service) _959873
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783030863647
776	0	8	_iPrinted edition: _z9783030863661
830		0	_aTheoretical Computer Science and General Issues, _x2512-2029 ; _v12893
856	4	0	_uhttps://doi.org/10.1007/978-3-030-86365-4 _3Springer Nature eBook _zOnline access link to the resource
912			_aZDB-2-SCS
912			_aZDB-2-SXCS
912			_aZDB-2-LNC
942			_cEBK
999			_c200459661 _d77873