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product_txtF_mv:"Springer eBooks 2005-"
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1
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part I
Published 2024
Springer Nature Singapore
Table of Contents:
“
... Connected Heterogeneous Graph Convolutional Neural Network -- Actor-Critic with variable
time
discretization...
”
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2
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part VIII
Published 2024
Springer Nature Singapore
Table of Contents:
“
...Theory and Algorithms -- Multi-model smart contract vulnerability detection based on BiGRU --
Time
...
”
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3
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XIV
Published 2024
Springer Nature Singapore
Table of Contents:
“
...MEFaceNets: Muti-scale Efficient CNNs for Real-
time
Face Recognition on Embedded Devices -- Optimal...
”
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4
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part IX
Published 2024
Springer Nature Singapore
Table of Contents:
“
... with Live-Oil Paintings --
Time
-Frequency Transformer: A Novel
Time
Frequency Joint Learning Method...
”
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5
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part II
Published 2024
Springer Nature Singapore
Table of Contents:
“
...Small-World Echo State Networks for Nonlinear
Time
-Series Prediction -- Preserving Potential...
”
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6
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part VII
Published 2024
Springer Nature Singapore
Table of Contents:
“
... Prediction -- Anti-Interference Zeroing Neural Network Model for
Time
-Varying Tensor Square Root Finding...
”
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7
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part X
Published 2024
Springer Nature Singapore
Table of Contents:
“
... hybrid
time
-frequency attention deep network -- A Feature Pyramid Fusion Network Based on Dynamic...
”
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8
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XV
Published 2024
Springer Nature Singapore
Table of Contents:
“
... Prediction via Classmates Augmented
Time
-Flow Hybrid Network -- Multiclass Classification and Defect...
”
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9
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part V
Published 2024
Springer Nature Singapore
Table of Contents:
“
... Framework Combining Retrieval and Generation -- Effi-Seg: Rethinking EfficientNet Architecture for Real-
time
...
”
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10
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XI
Published 2024
Springer Nature Singapore
Table of Contents:
“
... Computing Outsourcing and
Time
-Limited Access in Edge Computing -- An Ontology for Industrial Intelligent...
”
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11
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XIII
Published 2024
Springer Nature Singapore
Table of Contents:
“
...
Time
Series with a Novel Self-supervised Model based on Contrastive Learning -- Multimodal Event...
”
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12
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XII
Published 2024
Springer Nature Singapore
Table of Contents:
“
... for Multivariate
Time
Series Imputation -- Knowledge-Distillation-Warm-Start Training Strategy for Lightweight...
”
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13
Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part III
Published 2024
Springer Nature Singapore
Table of Contents:
“
... -- Privacy-Preserving Travel
Time
Prediction for Internet of Vehicles: A Crowdsensing and Federated Learning...
”
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Springer eBooks 2005-
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Li, Hongyi
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Luo, Biao
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