Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery

Name: Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery
Brand: Springer International Publishing AG
Price: 3682 SEK
Availability: InStock

Proceedings of the ICNC-FSKD 2022

AvNing Xiong,Maozhen Li

Springer International Publishing AG

2023

Del 153 i serien Lecture Notes on Data Engineering and Communications Technologies

3 682 kr

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Beskrivning

This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems, and knowledge discovery. The book is useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems, and knowledge discovery. The work printed in this book was presented at the 2022 18th International Conference on Natural Computation, Fuzzy Systems, and Knowledge Discovery (ICNC-FSKD 2022), held from 30 July to 1 August 2022, in Fuzhou, China. All papers were rigorously peer-reviewed by experts in the areas.

Produktinformation

Märke:Springer International Publishing AG
Utgivningsdatum:2023-01-31
Höjd:155 x 235 x 84 mm
Vikt:2 324 g
Språk:Engelska
Serie:Lecture Notes on Data Engineering and Communications Technologies
Antal sidor:1 508
Förlag:Springer International Publishing AG
EAN:9783031207372

Utforska kategorier

Artificiell intelligens inom Data och IT

Innehållsförteckning

Multiple Layers Global Average Pooling Fusion.- Han Dynasty Clothing Image Classification Model Based on KNN-Attention and CNN.- Self-attention SSD Network Detection Method of X-ray Security Images.- Cross Architecture Function Similarity Detection with Binary Lifting and Neural Metric Learning.- Pain Expression Recognition Based on Dual-channel Convolutional Neural Network.- A Noval Air Quality Index Prediction Scheme Based On Long Short-Term Memory Technology.- Code Summarization through Learning Linearized AST Paths with Transformer.- Function Level Cross-Modal Code Similarity Detection with Jointly Trained Deep Encoders.- Ease Solidity Smart Contract Compilation through Version Pragma Identification.- Towards Robust Similarity Detection of Smart Contracts with Masked Language Modelling.- DeSG: Towards Generating Valid Solidity Smart Contracts with Deep Learning.- Combining AST Segmentation and Deep Semantic Extraction for Function Level Vulnerability Detection.- A Novel Variational-Mode-Decomposition-Based Long Short-Term Memory for Foreign Exchange Prediction.