Big Data Technologies and Applications [electronic resource] : 13th EAI International Conference, BDTA 2023, Edinburgh, UK, August 23-24, 2023, Proceedings / edited by Zhiyuan Tan, Yulei Wu, Min Xu.

Colaborador(es): Tan, Zhiyuan [editor.] | Wu, Yulei [editor.] | Xu, Min [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ; 555Editor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XII, 192 p. 53 illus., 50 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031522659Tema(s): Computer networks  | Computer systems | Electronic digital computers -- Evaluation | Software engineering | Computer programming | Computer Communication Networks | Computer System Implementation | System Performance and Evaluation | Software Engineering | Programming TechniquesFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 004.6 Clasificación LoC:TK5105.5-5105.9Recursos en línea: Libro electrónicoTexto
Contenidos:
Infrared Few-shot Learning via Omnidirectional Compatible Class-Incremental -- Can Federated Models be Rectified through Learning Negative Gradients? -- BigText-QA: Question Answering over a Large-Scale Hybrid Knowledge Graph -- STLGCN: spatial-temporal Graph Convolutional Network for Long Term Traffic Forecasting -- Image Forgery Detection using Cryptography and Deep Learning -- Revocable Attribute-based Encryption Scheme With Cryptographic Reverse Firewalls -- IoT Attacks Countermeasures: Systematic Review and Future Research Direction -- A Bibliometric Analysis and Systematic Review of a Blockchain-Based Chain of Custody for Digital Evidence -- Forest Fire Prediction using Multi-Source Deep Learning -- Research on Preprocessing process for Improved image generation based on Contrast Enhancement -- An Auditable Framework for Evidence Sharing and Management using Smart Lockers and Distributed Technologies: Law Enforcement Use Case. A Review of the Non-Fungible Tokens (NFT): Challenges and Opportunities.
En: Springer Nature eBookResumen: This book constitutes the refereed post-conference proceedings of the 13th International Conference on Big Data Technologies and Applications, BDTA 2023, held in Edinburgh, United Kingdom, in August 2023. The 8 full papers and 3 short papers of BDTA 2023 were selected from 23 submissions and present new advances and research results in the fields of big data technologies, collection and storage, big data management and retrieval, big data mining and approaches.
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Infrared Few-shot Learning via Omnidirectional Compatible Class-Incremental -- Can Federated Models be Rectified through Learning Negative Gradients? -- BigText-QA: Question Answering over a Large-Scale Hybrid Knowledge Graph -- STLGCN: spatial-temporal Graph Convolutional Network for Long Term Traffic Forecasting -- Image Forgery Detection using Cryptography and Deep Learning -- Revocable Attribute-based Encryption Scheme With Cryptographic Reverse Firewalls -- IoT Attacks Countermeasures: Systematic Review and Future Research Direction -- A Bibliometric Analysis and Systematic Review of a Blockchain-Based Chain of Custody for Digital Evidence -- Forest Fire Prediction using Multi-Source Deep Learning -- Research on Preprocessing process for Improved image generation based on Contrast Enhancement -- An Auditable Framework for Evidence Sharing and Management using Smart Lockers and Distributed Technologies: Law Enforcement Use Case. A Review of the Non-Fungible Tokens (NFT): Challenges and Opportunities.

This book constitutes the refereed post-conference proceedings of the 13th International Conference on Big Data Technologies and Applications, BDTA 2023, held in Edinburgh, United Kingdom, in August 2023. The 8 full papers and 3 short papers of BDTA 2023 were selected from 23 submissions and present new advances and research results in the fields of big data technologies, collection and storage, big data management and retrieval, big data mining and approaches.

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